Why Botmetric Chose InfluxDB — A Real-Time Metrics Data Store That Works

Are you an engineer or an architect evaluating or seeking for a real-time data store featuring a simple operational management? If so, Botmetric recommends InfluxDB time series metrics data store. After years of trying out a couple of other data stores, Botmetric zeroed in on InfluxDB. Read on to know why Botmetric chose InfluxDB and what were the key criteria in using it over other data storage systems.

The Backdrop: Why Botmetric Chose InfluxDB Metrics Data Store?

Botmetric, the intelligent cloud management platform built for modern DevOps world, has always been helping cloud customers reduce overall cost, improve their security posture and automate day-to-day operations.

One of the unique differentiations of the Botmetric platform compared to other SaaS tools is the powerful automation framework, wherein DevOps teams can perform automated actions either based on real-time events or scheduled workflows.

To this end, Botmetric execute thousands of jobs every day for its customers to handle their tasks. This is expected to reach millions of tasks as the customer base grows. Further, the metadata around all Botmetric automations should be tracked continually to notify the end users and provide visibility into what’s done and what’s not.

Essentially, Botmetric delivers intelligent operations using the metadata from various operational sources like cloud providers, monitoring tools, logs, etc. It then applies concepts of Algorithmic IT Operations (AIOps) to provide smart insights and adaptive automation, so that the customers can make quick decisions. To that end, Botmetric collects a lot of time series data from different sources and is always in need of an efficient database solution.

Some time during early 2014, Botmetric was using OpenTSDB as a time series database solution. While team Botmetric liked the scalability aspect of OpenTSDB, they faced several challenges in operating it along with Hadoop, HBase, and ZooKeeper. So after 6 months, the team realized that OpenTSDB was not the right fit for a small and nimble team. Another major issue while using OpenTSDB was data aggregation, which was slowing down Botmetric’s development speed. Further, the lack of a reliable failover at HBase in 2014 had caused data availability issues.

In late 2014, team Botmetric decided to move away from OpenTSDB. Consequently, Cassandra & KairosDB was shortlisted as the alternative choice for storing the time series data. The team liked the quick setup and less operational burden compared to OpenTSDB in production. Plus, Cassandra offered with mature client libraries support for easier integration.

Even though Cassandra worked well for Botmetric until early 2016, the team had its share of challenges as the customer base with large data sets grew exponentially and data aggregation was becoming complex task. The Cassandra clusters had to be scaled vertically with high-end machines and horizontally with more nodes. More so, hundreds of millions of records had to be processed everyday into this data store while the team was still doing application level data aggregation on top of Cassandra using CQL. This was a time consuming exercise for most of the engineers in the team.

Further, from late 2015, Botmetric started moving away from metadata around cloud infrastructure, billing and usage records, etc. for easier and faster querying of data. The complete platform was decoupled into microservices-based architecture. To that end, we needed to stream data from our microservices, components usage, and monitoring metrics, etc. Botmetric’s search for reliable time series and real-time data store wasn’t achieved despite using Cassandra and KairosDB for over a year in production.

After several deliberations, during early 2015, Botmetric zeroed in on InfluxDB metrics data store. Botmetric deployed the InfluxData TICK stack with Grafana for monitoring of all the micro-services events. The Botmetric team loved the simplicity, ease of use, support for various client libraries, great aggregation capability for querying, the lack of operational overhead, and more that InfluxDB offered.

With InfluxDB, Team Botmetric was able to easily query data and aggregate it, unlike in Cassandra CQL. Above all, it offered auto expiry support for certain datasets. With this feature, Botmetric is now able reduce its DevOps effort in cleaning up old data using separate utilities.

In the words of Botmetric CEO Vijay Rayapati as cited in one of his blog posts, “InfluxDB is a savior. Its simplicity is amazing and will certainly speed-up your application development time. The simple operational management of InfluxDB will be very helpful if it’s a critical data store for you. You don’t need to break your head during any production debugging. Plus, their active community support is very helpful. We just loved what we saw with the TICK stack deployment for our SaaS platform metrics collection and events monitoring.”

Vijay further adds, “ We’ve now retired our entire KairosDB+Cassandra cluster and replaced it with an InfluxDB, Elasticsearch deployment. Today, InfluxDB and TICK stack are central components in the Botmetric technology landscape. We will continue to adopt it as our core data store as we build new real-time use cases that are event driven in nature.”

The Wrap up

Today, Botmetric refers to InfluxDB as good choice for “High Velocity Real-Time Metrics Data Store.” If you are an engineer or an architect looking for a real-time data store featuring a simple operational management, then your search should end at InfluxDB. You can read the detailed story here, if this case study interests you.

Editor’s Note: This blog post is an adaptation of Vijay Rayapati’s blog post, “Choosing a Real-Time Metrics DataStore That Works – Botmetric Journey.”

April Roundup @ Botmetric: Aiding Teamwork to Solidify 3 Pillars of Cloud Management

Spring is still on at Botmetric, and we continue to evolve like seasons with new features. This month, the focus was on how to bring in more collaboration and teamwork while performing various tasks related to cloud management. The three pillars of cloud management, visibility, control, and optimization, can be solidified only with seamless collaboration. To that end, Botmetric released two cool collaborative features in April: Slack Integration and Share Reports.

1. Slack Integration

What is it about: Integrating Slack collaboration tool and Botmetric so that a cloud engineer will never miss an alert or notification when on a Slack channel and quickly communicate/alert it to their team ASAP. 

How will it help: Cloud engineers can quickly get a sneak-peak into specific Botmetric alerts, as well as details of various cloud events, on their desired channel of Slack. Be it an alert generated by Botmetric’s Cost & Governance, Security & Compliance, or Ops & Automation, engineers can see these alerts without logged into Botmetric, and quickly communicate the problem between the team members.

Where can you find this feature on Botmetric: Under the Admin section inside 3rd Party Integrations.

To know more in detail, read the blogBotmetric Brings Slack Fun to Cloud Engineers

2. Share/Email Data-Rich AWS Cloud Reports Instantly

What is it about: Sharing/emailing Botmetric reports directly from Botmetric. No downloading required.

How will it help: For successful cloud management, all the team members need complete visibility with pertinent data in the form of AWS cloud reports. The new ‘Share Reports’ feature provides complete visibility across accounts and helps multiple AWS users in the team better collaborate while managing the cloud.

Where can you find this feature on Botmetric: Across all the Botmetric products in the form of a share icon.

To know more in detail, read the blog ‘Share Data-Rich AWS Cloud Reports Instantly with Your Team Directly From Botmetric.’

Knowledge Sharing @ Botmetric

Continuing our new tradition to provide quick bites and snippets on better AWS cloud management, here are few blogs that we covered in the month of April:

Gauge AWS S3 Spend, Minimize AWS S3 Bill Shock

AWS S3 offers a durability of  99.999999999% compared to other object storage on AWS, and features simple web interface to store and retrieve any amount of data. When it comes to AWS S3 spend, it has something more in it beyond just the storage cost. If you’re a operations manager or a cloud engineer, you probably know that data read/write or data moved in/out also do count  AWS S3 bill. Hence, a detailed analysis of all these can help you keep AWS S3 bill shock to a minimum. To know how, visit this page.

7 Tips on How to Work the Magic With DevOps for AWS Cloud Management

Are you a DevOps engineer looking for complete AWS cloud management? Or are you a AWS user looking to use DevOps practices to optimize your AWS usage? Both ways, AWS and DevOps are modern way of getting things done. You should leverage new age DevOps tools for monitoring, application performance management, log management, security, data protection and cloud management instead of trying to build adhoc automation or dealing with primitive tools offered by AWS.

Get the top seven tips on how to work the magic with DevOps for AWS cloud management.

The Ultimate Cheat Sheet On Deployment Automation Using AWS S3, CodeDeploy & Jenkins

If you’re a DevOps engineer or an enterprise looking for a complete guide on how to automate app deployment using Continuous Integration (CI)/Continuous Deliver(CD) strategies, and tools like AWS S3, CodeDeploy, Jenkins & Code Commit, then bookmark this blog penned by Minjar’s cloud expert.

Botmetric Cloud Explorer: A Handy Topological Relationship View of AWS Resources

Do you want to get a complete understanding of your AWS infrastructure. And map how each resources are connected and where they stand today for building stronger governance, auditing, and tracking of resources. Above all get one handy, cumulative relationship view of AWS resources without using AWS Config service. Read this blog how to get a complete topological relationship view of your AWS resources.

The Cloud Computing Think-Tank Pieces @ Botmetric

5 Reasons Why You Should Question Your Old AWS Cloud Security Practices

While you scale your business on cloud, AWS too keeps scaling its services too. So, cloud engineers have to constantly adapt to architectural changes as and when AWS updates are announced. While all architectural changes are made, AWS Cloud Security best practices and audits need to be relooked too from time to time.

Tightly Integrated AWS Cloud Security Platform Just a Click Away

As a CISO, you must question your old practices and relook at them whether it’s relevant in the present day. Here’re the excerpts from a think tank session highlighting the five reasons why you should question your old practices.

The Rise of Anything as a Service (XaaS): The New Hulk of Cloud Computing

The ‘Cloud-driven aaS’ era is clearly upon us. Besides the typical SaaS, IaaS, and PaaS offerings discussed, there are other ‘As-a-Service(aaS)’ offerings too. For instance, Database-as-a-service, Storage-as-a-Service, Windows-as-a-Service, and even Malware-as-a-Service. It is the era of Anything-as-a-Service (XaaS). Read the excerpts from an article by Amarkant Singh, Head of Product, Botmetric, featured on Stratoscale, which share views on XaaS, IaaS, PaaS, and SaaS.

April Wrap-Up: Helping Bring Success to Cloud Management

Rain or shine, Botmetric has always striven to bring success to cloud management. And will continue to do so with DevOps, NoOps, AIOps solutions.

If you have missed rating us, you can do it here now. If you haven’t tried Botmetric, we invite you to sign-up for a 14-day trial. Until the next month, stay tuned with us on Social Media.

Containerized Application Deployment on AWS using Docker Cloud


Docker Cloud, Docker Inc.’s hosted service that helps deploy and manage Dockerized applications, is widely used by DevOps engineers across the world. For the fact that it provides a registry with build and testing facilities for Dockerized application images. It also helps set up and manage host infrastructure, and deployment features to help automate deploying images to an infrastructure.

If you are a DevOps engineer looking to deploy containerized application on Amazon Web Service (AWS) using Docker Cloud, you are at the right place. Here’s a detailed step-by-step guide on how to go about it.

Your Docker Cloud Account and Docker ID

To start with, you need to log in to Docker Cloud using your free Docker ID. Your Docker ID is the same set of credentials you used to log in to the Docker Hub, and this allows you to access your Docker Hub repositories from Docker Cloud.

Images, Builds, and Testing

Docker Cloud uses Docker Hub as an online registry service. This allows you to publish Dockerized images on the internet either publicly or privately. Along with the ability to store pre-built images, Docker Cloud can link to your source code repositories and manage building and testing your images before pushing the images.

Infrastructure Management

Before you can do anything with images, you need to run them somewhere. So, Docker Cloud allows you to link to your infrastructure or cloud service provider, which lets you provision new nodes automatically, and thus help deploy images directly from your Docker Cloud repositories onto your infrastructure hosts.

For illustration, in this post, I am using Amazon Web Services (AWS) as the cloud service provider.

Step1. Link Docker Cloud with your Cloud Infrastructure

When you login to Docker Cloud, the below page appears.

Containerized Application Deployment on AWS using Docker Cloud

Click on first box (Link Provider), which is asking you to link to a hosted cloud service provider like DigitalOcean or AWS.

A page appears as shown below.

Containerized Application Deployment on AWS using Docker Cloud

Click on the plug shaped icon and fill your AWS Secret Key and Access Key (The Key associated to that user who have EC2 Full Access Policy attached).

Now, you’re ready to provision the nodes on AWS cloud.

Step2. Create a Node

Go back to the welcome page and click on the second box, which requests you to create a cluster node.

Click on Create and fill every details: Name of the node, details of the provider like AWS, Region, VPC, subnet-id, sec-group, instance type,IAM role, and node disk size, as well as the number of nodes you want.

And then click on Launch node cluster.

After some time you will get to see a page as shown below.

Now, when you take a peek into your AWS console, you will see three instances launched.

Step3: Create a Service

Go back to the welcome page and click on the third box, which requests you to create a service.

Click on Create Service button to open the Services/Wizard page as shown below.

Go to Miscellaneous section and click on dockercloud/hello-world. This will take you to the settings page as shown below.

Fill in the requisite details and go to Container configuration where you can set the entry point, memory limit, CPU limit and the command you want to run to spin up the container.

Now, publish the exposed port 80.

Note: If you want to link this container with another container, then you can use Links. And if you want to set any environment variable or want to attach or mount any volume, you can use Environment variable and Volume section. Once done, click on Create and Deploy. The below image will give you an idea.

When you click on Create and Deploy, your application service will deploy on all the three nodes created in Step 2.

At this moment, your containerized application is deployed on AWS. You can verify it by clicking on endpoints. The below image says it all!

And, voila! There you go.

See its very simple to deploy the containerized application on AWS in no time with Docker Cloud  ?

There are lot other features inside it like monitoring, autoscale, load balancing, etc. You can use these features when the deployment strategy needs to focus on high availability. Need help in deploying containerized application on AWS with the Docker Cloud? We at Minjar have your back! Do share your comments and thought with us on Twitter, Facebook or LinkedIn. You can drop in a comment below too.

P.S: Read my other blog post, Blue Whale Docker on AWS as CaaS, and How Enterprises Can Use it! to know how to leverage DDC as CaaS on AWS.

Top Five DevOps to NoOps Trends to Watch in 2017 and Beyond

2017 will be an exciting year for DevOps engineers. The astounding rise of containers, microservice architectures, and proliferation of machine intelligence is helping them solve their everyday problems. To this end, Ops & Automation is much simpler now. And with the fast-moving innovation paradigm that has set in over the years, the Ops community has seen the operational tasks evolving from traditional operations to new age DevOps. Primarily to suffice the need for more  agility and productivity. But with the rise of machine intelligence, another new trend is treading currently: DevOps to NoOps.

In the words of Botmetric CEO Vijay Rayapati, “NoOps is a logical progression of DevOps with the philosophy: Humans should solve new problems and the Machines should solve known problems!”

Vijay adds, “NoOps is an era of using intelligent automation for your operational tasks so you can eliminate the need for humans to manage operations, save precious engineering time, and solve known problems. As machines can make decisions on known problems and can provide diagnostic information for the new problems to reduce the operational overhead for engineers.”

Here’re the top five DevOps to NoOps adoption trends that every cloud engineer should know:

1. Serverless Programming: This programming and deployment paradigm will significantly eliminate the DevOps requirement for provisioning and configuration management. The cloud world will only see a growth trajectory for NoOps movement as all cloud vendors mature their serverless offerings.

2. Containerization: The containers like Docker will further abstract the dependencies and resource sharing between different components by leveraging cluster management and orchestration solutions like Kubernetes, Mesos, ECS, Nomad, etc. to provide a common view of underlying infrastructure.

3. Microservices Architecture: It will help engineers and companies to decouple the complexity of monolithic systems into small yet manageable components handling specific responsibility. As containerization becomes standard way of deploying components in the cloud, it will see rapid adoption.

4. Intelligent and Unified Operations: Static tooling with (no intelligence) is slowly growing on to the engineers and getting on their nerves To this end, there has been a  rise in the use of machine intelligence, and increased adoption of deep learning. Consequently, the industry will see more adoption of dynamic tooling that can ultimately help them in day-to-day operations.

5. Self Healing and Auto Remediation: Earlier, DevOps world was limited to build, deployment and provisioning while the day-to-day operations were handled in a manual or semi-automated fashion. Now it’s about time, engineers embrace NoOps where machines can resolve known, repetitive problems and engineers can solve new problems.

To delve further deep into DevOps to NoOps trends, read the post by Botmetric CEO Vijay Rayapati, where Vijay will throw light on the details of all the five trends shaping the cloud world in 2017 and beyond.

Which other technologies do you think will trend this year in the cloud arena? Do drop in your thoughts in the comment section below or tweet to us at @BotmetricHQ.

Editor’s Note: This exclusive blog post is an adaption of the original article, The 2017 Cloud Trends: DevOps to NoOps, penned by Botmetric CEO Vijay Rayapati.

Blue Whale Docker on AWS as CaaS, and How Enterprises Can Use it!

We live in an exciting era of data centers and cloud operations. And in these data centers, innovative technologies such as Docker containers eliminate all the superfluous processes that can bog down a machine and enable servers to live up to their potential. With the availability of Docker Datacenter (DDC) as Container-as-a-Service (CaaS), the excitement among enterprises is more than ever.

Making Sense of Docker Datacenter (DDC) as Container-as-a-Service (CaaS)

As you may know, containers make it easy to develop, deploy, and deliver applications that can be deployed and brought down in a matter of seconds. This flexibility makes it very useful for DevOps team to automate continuous integration and deploy containers.

And Docker datacenter offering, which can be deployed on-premise or in the cloud, makes it even more easier for enterprises to set up their own internal CaaS environments. Put simply, the package helps to integrate Docker into enterprise software delivery processes.

Basically, the CaaS platform provides both container and cluster orchestration. And with the availability of cloud templates pre-built for the DDC, developers and IT operations staff can move Dockerized applications not only into the cloud but also into and out of their premises.

Below is the brief architecture that DDC offers:

Docker Datacenter Architecture
Image Source: Docker | https://www.docker.com/products/docker-datacenter

A pluggable architecture provides flexibility in regards to compute, network, and storage, which are generally a part of a CaaS infrastructure. Moreover, the pluggable architecture provides flexibility without disrupting the application code. So, enterprises can leverage existing technology investments with DDC. Plus, the Docker Datacenter consists of integrated solutions including open source and commercial software. And the integration between them includes full Docker API support, validated configurations, and commercial support for DDC environment. The open APIs allow DDC CaaS to easily integrate into an enterprise’s existing systems like LDAP/AD, monitoring, logging, and more.

Before we move to comprehending Docker on AWS, it is advisable to have a look at the pluggable Docker Architecture.

Pluggable Docker Architecture.
Image Source: Docker

As we can see from the image, DDC is the mixture of several Docker Project:

  • Docker Universal Control Plane [UCP]
  • Docker Trusted Registry [DTR]
  • Commercial Supported Docker Engine [CSE]

The Universal Control Plane (UCP)

The UCP is a cluster management solution that can be installed on-premise or on a virtual private cloud, says Docker. The UCP exposes the standard Docker API so that you can continue to use the tools that you already know to manage an entire cluster. With the Docker UCP, you can still manage the nodes of your infrastructure as apps, containers, networks, images, and volumes.

The Docker UCP has its own built-in authentication mechanism, and it supports LDAP and Active Directory as well. But, as role-based access control (RBAC). This ensures that only authorized users can access and make changes to the cluster.

In addition, the UCP, which is a containerized application, allows you to manage a set of nodes that are part of the same Docker Swarm. The core component of the UCP is a globally-scheduled service called ‘ucp-agent.’ Once this service is running, it deploys containers with other UCP components and ensures that they continue to run.

DDC Universal Control Panel in Architecture
Image Source: Docker.com

Docker Trusted Registry (DTR)

DTR allows you to store and manage your Docker images, either on-premise or in your virtual private cloud, to support security or regulatory compliance requirements. Docker security is one of the biggest challenges that developers face when it comes to enterprise adoption of Docker. The DTR uses the same authentication mechanism as the Docker UCP. It has a built-in authentication mechanism and integrates with LDAP. It also supports RBAC. This allows enterprises to implement individualized access control policies as necessary.

Commercial Supported Docker Engine (CSE)

CSE is nothing but a normal legacy Docker engine with commercial support and additional orchestration features.

For many enterprises, it seems that more the components in the architecture, more complex it gets. Hence, the deployment of DDC will be very painful. It’s a myth! Thanks to AWS and Docker. They already had prepared the recipe to deploy the entire DDC on AWS with the best practices of AWS. The recipe is prepared in CloudFormation Template by taking care of enhanced security. Below diagram shows the overall commercial architecture.

Cloud Formation Template for a Commercial Architecture
Image Source: AWS

For a detailed resource utilization, enterprises need to just checkout the CloudFormation Stack Architecture as shown below. This seems very complex, but this is the most secure approach for the sake of enterprise production. To get the infrastructure ready, one has to Launch a Stack.

Cloudformation Stack Architecture
AWS CloudFormation Stack Architecture

The CloudFormation template will create the below resources and activity:

  • Creates a new VPC, private and public subnets in different AZs, ELBs, NAT gateways, internet gateways, AutoScaling Groups- all based on AWS best practices
  • Creates and configures a S3 bucket for DDC to be used for cert backup and DTR image storage
  • Deploys 3 UCP controllers across multiple AZs within VPC and creates a UCP ELB with preconfigured HTTP healthchecks
  • Deploys a scalable cluster of UCP nodes, and backs up UCP Root CAs to S3
  • Creates a 3 DTR Replicas across multiple AZs within VPC, and creates a DTR with preconfigured healthchecks
  • Creates a jumphost EC2 instance to be able to SSH to the DDC nodes
  • Creates a UCP Nodes ELB with pre-configured health checks (TCP Port 80). This can be used for your application that are deployed on UCP
  • Deploys NGINX+Interlock to dynamically register your application containers
  • Creates a CloudWatch Log Group (called DDCLogGroup)and allows log streams from DDC instances. It also automatically logs the UCP and DTR installation containers

A click on Launch Stack will redirect the user to AWS console where he/she will get the CloudFormation template page with already filled Amazon S3 template URL.

Cloudformation template page

After getting the Status of the Stack as CREATE_COMPLETE, he/she needs to click on Outputs to get the Login URL of UCP and DTR. Refer the image below:

Login URL of UCP and DTR


After the UCP Login, the user will get a secure login web page as shown below:

Secure Docker Login Webpage

A beautiful, detailed Control Panel will appear as shown below:

A beautiful detailed Control Panel


And a DTR panel will look something like this:

DTR Panel

Viola!!! Now, Docker DC (as CaaS) is ready to use on AWS host.

As a DDC user, you must be thinking, why anyone will go for the DDC for the Deployment of Application. Here’s why: The technology that makes the application more robust and nimble will be considered as the king. And with the adoption of microservices architecture,  your application will be the most competitive.

To set the context here: Nowadays, Docker is considered as one of the best containerization technologies to deploy microservices-based applications. While implementing it, there are few key steps that needs to be followed. They are:

  1. Package the microservice as a (Docker) container image.
  2. Deploy each service instance as a container.
  3. Perform scaling, which is done based on changing the number of container instances.
  4. Build, deploy, and start a microservice, which is much faster than a regular VM.
  5. Write a Docker Compose file where we will mention all the image and their connectivity and then just build it.

Lots of enterprises are now considering to refactor their existing Java and C++ legacy applications by dockerizing them and deploying them as containers, says Docker. Hence, this technology was built to provide a distributed application deployment architecture that can manage workloads, plus can be deployed in both private and eventually public cloud environments.

In this way, DDC solves lots of problems today’s enterprises face, including BBC, Splunk, New Relic, Uber, PayPal, eBay, GE, Intuit, New York Times, Spotify, etc.

For demo purpose, Docker provides users with options to deploy a microservice application for different services, such as:

  • A Python web app that lets you vote between two options
  • A Redis queue that collects new votes
  • A Java worker who consumes votes and stores them in
  • A Postgres database backed by a Docker volume
  • A Node.js web app that shows the results of the voting in real time

Here’s how: After going to the Resource of UCP, click on Application and then + Deploy Compose.yml

Docker resources dashboard

Hit the name of the application and write down the docker compose yaml. Or, you can also upload the file and click on create. After sometime, you will be able to see some logs, and then the application will be deployed.

In below image, we can see that 5 containers were spinned-up at the time of deployment of the application. Each and every container have their own services and worker.

Docker dashboard

If you want to try to hit the application from a web browser by getting the exact IP and Port, refer the image below:

Docker Dashboard


By performing this activity, the application will be up and running. Refer the illustration below:

An Illustrative App
An Illustrative App

If you want to modify it in code, you can modify it from the Web UI. This means that you can access the container CLI from Web as well.

Accessing the container CLI from Web

To Wrap Up:

DDC as CaaS is changing the delivery process of containerized application among the enterprises. The idea is that Docker wants to make it easy for enterprises to set up their own internal Containers-as-a-Service (CaaS) operations.

Are you an enterprise looking to leverage DDC as CaaS on AWS? As a Premier AWS Consulting Partner, we at Minjar have your back! Do share your comments and thought with us on Twitter, Facebook or LinkedIn. You can drop in a comment below too.

References used:

  • https://github.com/nicolaka/ddc-aws
  • https://github.com/docker/docker-birthday-3/tree/master/example-voting-app
  • https://www.docker.com/sites/default/files/RA_UCP%20Load%20Balancing-Feb%202016_1.pdf

Top 5 Reasons Why AWS for Fintech is a Perfect Match

Banking & Finance industry has been one of the very early adopters of technology since the boom began two decades ago. To complement and support the massive banking & finance industry, Fintech emerged during the turn of the millennium to bring in more efficiency, transparency & accountability in how the industry functions. Today, banks are embracing and co-opting with their Fintech disruptors to manage massive technology trends like Cloud, Mobile and Blockchain to stay afloat in a market driven by disruptive tech. And by adopting AWS for Fintech is like a match made in heaven. Plus, these banking and finance companies can accelerate their “go to market” and lower costs in a short duration.

The Context: Unbundling the Banks and Finance Companies with Fintech

To set the context here, banking and finance is quickly adopting digital transformation solutions, like all other industries. Fintech startups in particular are taking part in “unbundling of the Bank” with each startup offering only a specific selected function of the traditional banks like payments processing, remittances etc.

Above all, Fintech companies are innovating within that standalone specified service space. There are many classic cases for disruption, however, major banks are encouraging Fintech players instead of seeing them as threats by adopting strategies like acquiring the successful ones. One of the major reasons for this embracing strategy of big banks is their own technology legacy, which is holding them back from moving as fast as startups.

AWS for Fintech: Why?

Fintech startups have the advantage of building on cutting edge technologies like cloud, mobile and blockchain as they do not have any legacy systems to support. On the other hand, already established Fintech companies too are realizing the benefits of AWS cloud, due to the low capex cost associated with it, further making AWS Cloud a very attractive computing infrastructure.

If you are a IT decision maker or a DevOps professional in a Fintech company contemplating AWS cloud, then read on these top 5 reasons why you must adopt AWS Cloud:

1. One Click Regulation & Compliance

On the AWS cloud, security is of the highest priority. AWS users can benefit from the data center and network architecture built to meet the requirements of the most security-sensitive organizations. AWS cloud compliance enables customers to understand the robust controls in place. Additionally to maintain security and data protection in the cloud, AWS provides cloud formation templates which have standard three-tier web architecture for PCI DSS on AWS depicting integration with multiple VPCs.

Using the AWS cloud formation tool, you can deploy the secure architecture with a click of button. While AWS manages security of the cloud infrastructure, the security of the apps on it however is your responsibility. You can retain control of what security to implement, in order to protect the content, platform, applications, systems and networks.

Above all, you can create virtual banking platforms that meet payment card industry (PCI) data security standard (DSS) compliance by leveraging architectures from AWS cloud compliance. AWS can automate processes that once took months to complete and lets you to focus on core value proposition and customer service rather than managing the IT infrastructure.

2. Seamless and Safe Transaction Data Backups

Banking and finance industry is all about transactions. The transactional data, which are generated through the transactions have to be archived and saved securely for future retrieval. The database of the transactions has to be stored complying the disaster recovery regulations at different geographical zones. Moreover, processes should be established to ensure that recovery will be accomplished within a short duration, if at all there is any disruption. With AWS’ strong Disaster Recovery (DR) policies, it is piece of cake.

In addition, highly secure and fault tolerant backups and DR is one of the major use cases for cloud platforms like AWS. As a Fintech co., you need not worry about the long procurement and provisioning cycles of data centers for Backup. Further, AWS provides huge savings for Fintechs just in Information Security Compliance use case.

3. Performance and scaling

Most of the Fintech companies are consumer facing i.e B2C startups. You must be already aware that the usage patterns of the applications will face many spikes and bursts. To cater to such needs, AWS provides auto-scaling feature, which ensures consistent performance even during those surge periods.  It can automatically increase the number of Amazon EC2 instances during demand spikes to maintain performance and decrease capacity during lulls to reduce costs. Auto scaling is ideal for applications that have stable demand patterns or that experience hourly, daily, or weekly variability in usage. Moreover, the auto scaling feature is one of the best AWS Cost Optimization feature, which helps you save more as you scale.

4. 24 x 7 x 365 Availability

With the democratization of mobile phones, it is evident that Fintech companies’ services have to be available 24 x 7 x 365, just to ensure that customers can access services anywhere, anytime. AWS auto scaling can help Fintech companies to maintain application availability while also allow them to scale the AWS EC2 capacity up or down automatically according to customer usage patterns. However, by leveraging auto scaling, Fintech companies can ensure that their apps are running on optimal number of AWS EC2 instances, resulting in effective AWS Cloud Management. Ultimately, AWS ensures Fintech companies’ services are available 24 x 7 x 365.

5. Supporting DevOps Culture

Rapid rollout of new features is one of the key value propositions for Fintech companies. Could not agree more? And to achieve rapid roll-outs, Fintech companies have to embrace DevOps processes. AWS provides built in support for DevOps by providing ready-to-use complete tool chain. This AWS DevOps tool chain consists of AWS code commit for hosting a private git for their code base, AWS code pipeline Continuous delivery service to automatically build, test etc. and AWS CodeDeploy for automating the code deployment to any EC2 Instance.

AWS for FinTech: Made for each other

With such impeccable capabilities along with entire software development life cycle support from development to deployment, AWS is definitely a perfect match for Fintech companies to stride through the path of digital transformation.

If you are an IT decision maker or a DevOps professional in a Fintech company that is already on AWS, then you might as well explore Botmetric, the only cloud management platform that simplify day-to-day cloud operations while also help with other AWS Cloud Cost optimization, performance monitoring tasks, etc. To know how Botmetric facilitates with automated backups, DR, etc. then try the 14-day trial today. Do share your thoughts with us on Twitter, Facebook or LinkedIn.  

DevOps in AWS Cloud is a Match Made in Heaven

Every organization, who wants to execute DevOps into their cloud business, can take benefits from AWS, as it is rightly said that DevOps in AWS Cloud is a match made in heaven. But t the same time, it is very important for organizations to be committed so that their business runs smoothly.

DevOps techniques are unique and designed to suit the modern age business requirements. They combine very well with the AWS’s flexibility, operation, and wide range of tools and options.  They also guarantee streamlining the deployment and automate code updates. So a link between the DevOps technology and AWS is truly a match made in heaven for cloud users.

But, how do these two entities work to deliver the agility required by enterprises to run their business in cloud? AWS Elastic Beanstalk supports rolling deployments. This is a very common DevOps practice that allows configuration deployments to work with AWS Auto Scaling. Thus, there a certain number of instances are always ready and accessible. Even with other many configuration changes, instances are available. This implies that as soon as Elastic Compute Cloud (EC2) instances are updated, the developer stays in control. For any change in EC2 instance type, the developer can easily make out if Elastic Beanstalk has restructured all instances or is maintaining some instances running to serve requests; in the meantime, other instances are being updated. Whenever any deployments are made, AWS OpsWorks enables developers to define about instances layers to be updated. It is another example that shows how the public cloud supplier supports the DevOps mindset.

Apart from this, it has been observed multiple times by many experts that there is a natural fit with DevOps in AWS Cloud that opens a path to agility.

Let’s see how AWS simplifies DevOps process:

Public clouds let enterprise to take advantage of their advanced technology. Enterprises might access or afford those technologies if not for Cloud. AWS’s on-demand assets and scalability facilitates DevOps. There are several capabilities that organizations can make use of while working with DevOps in AWS Cloud. Let’s analyze some of them:

  • DevOps gives businesses the capability to rapidly position latest environments and configurations required for implementation of new features and functionality. Doing this through AWS enables enterprises to break down environments when they are no longer required. This also removes the requirements and associated expense. Thus, keeps a range of internal hardware and infrastructure accessible and manages the effects of hardware acquisition delays.
  • Through DevOps in AWS Cloud, all team members can easily test out new deployment packages without disturbing the operational environment.
  • DevOps allows testing in AWS through which teams can simply shift and deploy to the internal cloud execution.
  • DevOps provides the capability to supplement resource abilities during the periods organizations face peak demand.
  • DevOps ensures that your environments are provisioned with precisely the resources your business needs. It integrates the test streams and run the tests at the same time.
  • DevOps identifies any possible conflicts while allowing AWS to pool resources and share the results.
  • Finally, it also automates the advertising of the application to the next stage of the lifecycle within the workflow.

Thus, DevOps in AWS Cloud makes certain that your business competes in this new economy. As DevOps is impetus to cloud security, by effectively incorporating the best practices it ensures business agility. DevOps allow you to keep a track so that you get alerted whenever there is any requirement and Botmetric promises the flexibility of automating tasks in fraction of a minute!

With Botmetric Cloud Automation, you can enjoy the freedom of saving up more time in automating your routine cloud tasks. At the same time, Botmetric fixes cloud issues in just the click of a button to help users better optimise, simplify, and automate their tasks on cloud.

Take up a 14-day free trial to learn how Botmetric in your AWS Cloud environment can simplify your CloudOps and DevOps tasks 10x faster!

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DevOps Culture is Impetus to Cloud Security

Embracing DevOps culture and implementing Automation offers very helpful prospects to improve functional excellence and time-to-market. In addition to these, expenses are abridged in several dimensions like employees costs, assets costs, value costs, intricacy costs, and, most imperative in the eyes of many industry leaders, the time costs.

DevOps has now emerged as a key part of enterprise IT planning. The simple pragmatic way of managing security in an atmosphere that is developing so fast and changing so swiftly is to make it automation first. Botmetric offers facility to schedule Cloud Automation jobs for all the use cases. With our AWS DevOps Automation, you can easily manage your everyday cloud tasks with just a click. Not only this, but you can alleviate impending security concerns while preserving high velocity and quick time-to-market on the side of your business.

You might be following the necessary security best practices. Still, given that a huge volume of resources are tailored and instigated in your AWS cloud infrastructure every day, there is a probability that you would have failed to notice some imperative security best practices. Now, there is no need to manually check that your security best practices are being followed or not. Botmetric’s wide-ranging AWS cloud infrastructure security audit features have them automatically scanned on a daily basis and generate violations list. This will help you in implementing new required security methods along with tweaking your active security plan. It makes sure that your AWS Cloud infrastructure runs efficiently and is completely sheltered from any severe security threats and data violations.

Here’re few measure you can take to deal with issues of cloud privacy:

  • Avoid storing sensitive information in the cloud
  • Try keeping your critical information away from virtual world or use appropriate solutions.
  • Read the user agreement carefully to understand how your preferable cloud service storage works
  • There is no doubt it is going to be boring but you really need to read it carefully to decide which cloud storage to choose
  • Be serious about passwords
  • Never forget your password or use the same password for two emails as it can serve as a real trap sometime


Encryption is, up to now, the best way to protect your data in cloud

Security is a meadow where there are a lot of conclusions and choices that industries need to make and they might need to change their strategies in real-time. Botmetric’s well-designed security management is helping organizations in understanding the importance of security specifically and enabling them in incrementally advancing towards their needed posture.

Take the risk out of your cloud infrastructure through Botmetric’s extensive list of foremost security checks. These security checks are carried out on a regular basis. Let Botmetric help you in ensuring safety of your AWS Cloud infrastructure by providing you concrete report for all your cloud insights.

Get started with a 14-day free trial, today!

Having A Disaster Recovery Plan Is Pivotal – The Do’s And Don’ts On AWS Cloud

Disaster, be it a tornado or a human error, can be destructive. Many companies have gone out of business after losing their mission critical data due to disasters hitting their data centers. Hence, in this digital world, having a disaster recovery plan in place is pivotal to any organization’s success. The best you can do is be prepared for any disaster.

While most enterprises are getting ready and recuperating from any negative impact or disaster possibilities, there are customers who are on cloud but are unaware of the best approaches towards strategizing their disaster recovery plans effectively. No worries!

Here are the Do’s and Don’ts that you must keep in mind while planning your next DR Strategy on AWS Cloud.

Disaster recovery plan – The Do’s

Back up your data into AWS with the right tool/technique

Before a disaster hits one of the AWS regions and you lose all of your critical data, make sure you have backed up your data to multiple other regions. The frequency of backing up of your data would largely depend on the Recovery Time Objectives (i.e., how quickly you want the data asset to be recovered) and your preferred Recovery Point Objectives (i.e, how fresh the recovery of the asset must be, like, zero data loss, 15 mins out of date, etc).

If your DR strategy is automated to take up routine file backups, the recovery point would be the time when the latest backup was uploaded to cloud storage. Similarly, if you are taking up redundant backups of data between databases, the recovery point would automatically be the last operation done on the standby database.

Audit your Cloud Infra

In simple words, disaster in any form is a disaster. Human error, innovation failure, DR planning can go haywire at any point of time. With well-planned DR strategies in place, businesses can become DR-ready to handle any emergency. Botmetric recommends you to run routine DR/Backup audit to make sure all your mission-critical data on AWS Cloud is safe and secure.

Backup Everything

Don’t just focus on data! Take a backup of all your IT infrastructure modules, essential application settings, etc. it is highly recommended to periodically copy your data backups across the AWS regions.

With Botmetric, you can do so by scheduling a job for cross-region copy:

  1. Copy EBS Volume snapshot (based on volume tags) across regions
  2. Copy RDS snapshot (based on RDS tags) across regions

Test Your DR Plan

Automate your DR plan so that your business is disaster-proof. Identify the crucial areas that you feel might get affected if a disaster hits, and try and automate the tests for that particular area. Periodic testing will ensure that all policies, including RTO and RPO, are aligned properly. Botmetric DR audit runs an extensive list of audits for your AWS Cloud Infra and in turn automates the DR/Backup tests. This ensures you stay up-to-date with the health of your cloud infrastructure.

Disaster recovery plan – The Don’ts

Stop Procrastinating

Disaster will not knock at the door before it strikes. Therefore, don’t let disaster recovery planning take a back seat. Having a DR strategy in place and testing your AWS architecture will make sure all your data stick through you even when disaster strikes.

Don’t Just Plan For the Sake Of Planning

For business continuity, most of the enterprises are having a DR plan. But, simply having a plan without a strategic approach can put your business at risk. An ideal approach would be to keep all security measures in place and audit your cloud infra regularly. Botmetric DR/Backup audit ensures data safety by enforcing data retention and backup policies, across geographically distributed cloud resources.

Avoid Single-Region Replication

In order to survive the worst cloud outage, it is highly recommended that you copy your data across regions. It means if data loss occurs at one region, you can access your lost data from the second backup region. This is perhaps the best strategy to survive from extreme cloud outages, even if failure occurs in an entire AWS region.

These are some of the practical do’s and don’ts that you should practice to back up data in the cloud with ease. With timely automation of DR backup tasks and the right strategy in place, you can safely make your AWS Cloud Infrastructure DR ready. Botmetric can help.

So what are you waiting for? Sign Up for Botmetric 14-day trial and make your business on AWS Cloud ‘disaster-proof’.

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AWS Cloud DevOps Automation

How do you ensure timely backup of your RDS/EBS data? Do you copy your AWS snapshots across regions to be disaster recovery ready? Botmetric provides ability to schedule Cloud Automation jobs for all these use cases and more.

Here are all the cloud automation jobs which will help you to save time and improve your operational agility.

Take EBS volume snapshot based on instance/volume tags

It is recommended that you enable regular snapshots for your AWS EBS volumes. Using Botmetric’s Cloud Automation you can schedule a job which will create snapshots automatically for the EBS volumes having specified instance or volume tags. This would also help you to be DR ready.

For further instructions click here.

Take RDS snapshot based on RDS tags

You should make sure that you enable regular snapshots for your AWS RDS instances. Using Botmetric’s Cloud Automation you can schedule a job which will create snapshots automatically for the RDS instances having specified tags.

For further instructions click here.

Stop EC2 Instances based on instance tags

You might have several workloads on AWS cloud which you would not need on certain days of the week. For example, your dev instances might not be required to be up on weekends. In these cases, it is better to take advantage of hourly billing of AWS cloud and stop those instances and save some cost. Using Botmetric’s Cloud Automation you can schedule a job which will stop EC2 instances automatically at specified time.

For further instructions click here.

Start EC2 Instances based on instance tags

If you have used the above feature, then it is natural that you would want to start your stopped instances on desired schedule. For example, all the dev instances which you had stopped on Friday night can be started on Monday morning. Using Botmetric’s Cloud Automation you can schedule a job which will start EC2 instances automatically at a specified time.

For further instructions click here.

Create AMI for EC2 Instances based on instance tags

You can schedule creation of AMI for EC2 Instances based on instance tags automatically.

For further instructions click here.

Copy EBS Volume snapshot (based on volume tags) across regions

You can take your disaster recovery strategy to a higher level by enabling your data backups to be copied across AWS regions. Using Botmetric’s Cloud Automation you can schedule a job which will automatically on specified periods copy EBS Volume snapshot based on volume tags from a source region to the destination region.

For further instructions click here.

Copy RDS snapshot (based on RDS tags) across regions

Using Botmetric’s Cloud Automation you can schedule a job which will automatically on specified periods copy RDS snapshot based on RDS tags across regions.

For further instructions click here.

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