As businesses embrace microservices and cloud-native architectures, DevOps stands at the center, helping businesses efficiently manage IT workloads. DevOps is an innovative methodology that integrates development, operations, security and business teams to seamlessly coordinate and deliver quality products faster and better. From planning and development to delivery and operations, DevOps works right through the entire application lifecycle.
DevOps brings developers and operations together so that the code is automatically build, tested and deployed in a continuous model. It uses a Continuous Integration / Continuous Deployment (CI/CD) pipeline with automation incorporated across the product lifecycle to accelerate the development process and improve efficiencies while reducing costs.
A CI/CD pipeline comprises a series of steps involved in the delivery process of quality software. It includes the following steps:
- Build Phase: The application code is build and compiled here
- Test Phase: The compiled code is tested here
- Release Phase: The code is pushed to the repository
- Deploy Phase: Code is deployed to production
While DevOps offers amazing benefits to IT teams, many organizations fail to leverage it owing to a lack of understanding of this methodology. Understanding different categories of DevOps and implementing the right tool stack is important. Here are 3 important DevOps categories every organization should focus on.
1) Software DevOps
Software DevOps is where the core software is developed. It involves planning the design, assigning tasks to the team and creating artefacts using tools such as coding software, integrated development environment (IDE), version control system, testing framework and issue management.
Integrated Development Environment (IDE): Developers use a text editor to write, debug and edit code. However, an IDE comes with much more features than a text editor offers. Along with an editor, the IDE offers debugging and compilation enabling you to build, test and deploy code from a single dashboard. Choosing the right IDE improves productivity, reduces errors and eases the development process. While choosing an IDE, ensure that it can be integrated with services across the DevOps lifecycle. Visual Studio, IntelliJ and Eclipse are some of the popular IDEs available in the market.
Version Control System: When multiple developers work on a software project, keeping track of code changes becomes a critical requirement. A version control system helps you to keep track of each code change and revert to a specific version when a release crashes. Git is the most popular VCS system. CVS, Mercurial and SVN are other options available in this segment.
Testing Framework: A testing framework offers a set of guidelines to design and run test cases using the best testing tools and practices.
Issue Management: It is a process of identifying system-level conflicts and defects in the workflow based on events or metrics. It involves detection, response, resolution and analysis.
To achieve continuous delivery, it is important to choose the right CI/CD tools and implement automation wherever possible. Here are a few best tools for software DevOps:
Jenkins is an open-source CI server tool that comes free of cost. It supports Linux, Windows and macOS platforms as well as major programming languages. The main advantage of Jenkins is its plug-in repository. You can find a plugin for most of the development tasks. Moreover, it can be easily integrated with other CI/CD platforms. Debugging is easy. However, it is important to check if the plug-ins are updated. Another downside is the lack of a user-friendly UI. It has a learning curve concerning the installation and configuration of the tool.
Github Actions is a CI/CD platform that enables developers to directly manage workflows in their Github repository. As such, you can perform repository-related tasks in a single place. It offers multiple CI templates. Github Actions comes with 2000 build minutes free per month.
GitLab is a CI software developed by GitLab Inc. for managing DevOps environments. It is a web-based repository that enables administrators to perform DevOps tasks such as planning, source code management, operations, monitoring and security while facilitating seamless coordination between various teams through the product lifecycle. This platform was written in Ruby and launched in 2014 as a source code management tool. Within a quick time, it evolved as a platform that covers the entire DevOps product lifecycle. It comes with an open-core license which means the core functionality is open-source and free but additional functionalities come with a proprietary license.
AWS Code Pipeline
AWS CodePipeline is a powerful DevOps product from AWS that enables developers to automate and manage the entire product lifecycle. The tool automatically creates a build, runs the required tests to launch an app whenever a code change is detected. It offers an intuitive GUI dashboard to efficiently monitor and manage workflow configurations within the pipeline. As AWS CodePipeline is tightly integrated with other AWS services such as S3, Lambda or 3rd party services such as Jenkins, it becomes easy to create quality software faster and better. You can simply pull code from S3 and deploy it to Elastic Beanstalk or Codedeploy.
2) Infrastructure DevOps
Infrastructure management is another crucial component of a DevOps environment. With the advent of Infrastructure as Code (IaC), managing the infrastructure became simple, cost-effective and risk-free. Infrastructure as Code is an IT method of provisioning and managing infrastructure resources via config files, treating infrastructure as software. IaC enables administrators and developers to automate resource provisioning instead of manually configuring hardware. Once the hardware is transformed into software, it can be versioned, rollback and reused.
The advent of Ruby on Rails and AWS Elastic Compute Cloud in 2006 enabled businesses to scale cloud resources on-demand. However, the massive growth in web components and frameworks posed severe scalability challenges as administrators struggled to version and manage dynamically changing infrastructure configurations. By treating infrastructure as code, organizations were able to create, deploy and manage infrastructure using the same software tools and best practices. It allowed rapid deployment of applications.
IaC can be implemented using two models namely Declarative Configuration and Imperative configuration. In a declarative approach, the configuration is defined in a declarative model that shows how the infrastructure should be while the Imperative model defines steps to reach the desired state. Terraform and AWS CloudFormation are the two most popular IaC tools that enable organizations to automatically provision infrastructure using code.
Infrastructure as Code took infrastructure management to the next level. Firstly, it rightly fits into the DevOps CI/CD pipeline. The ability to use the same version control system, testing frameworks and other services of the CI/CD pipeline facilitates seamless coordination between various teams and faster time to market while significantly reducing costs. It also helps organizations leverage the containerization technology wherein the underlying infrastructure is abstracted at the OS level, and the hardware and OS are automatically provisioned. As such, containers running on top of it can be seamlessly deployed and moved across a wide variety of environments.
Secondly, IaC offers speed and efficiency with infrastructure automation. It is not confined to compute resources but extends to network, storage, databases and IAM policies as well. The best thing about IaC is that you can automatically terminate resources when they are not in use. Thirdly, IaC reduces operational costs as the number of network and hardware engineers required at every step of operations is reduced. Fourthly, it brings consistency across all deployments as config files use a VCS as a single source of truth. Scalability and availability are improved. Monitoring the performance and identifying issues at a granular level helps reduce downtimes while increasing operational efficiencies. Overall, it improves the efficiency of the entire software development lifecycle.
Terraform is an open-source IaC tool developed by Hashicorp in 2014. Written in Go language, Terraform uses Hashicorp Configuration Language (HCL) to define the desired state of the target infrastructure on a variety of platforms including Windows, Solaris, Linux, FreeBSD, macOS and OpenBSD. Terraform is a declarative-based tool that stores the state of the infrastructure using a custom JSON format along with details of which resources should be configured and how. The tool uses ‘Modules’ to abstract infrastructure into sharable and reusable code. HCL is human-readable and helps you quickly build infrastructure code. Terraform is cloud-agnostic and integrates well with AWS. So, it can be used to manage a variety of cloud environments.
AWS CloudFormation is a managed IaC service from AWS that helps you to create and manage AWS resources using simple text files. Along with JSON template format, YAML is supported. AWS constantly updates the tool to always keep it current while adding several new features regulalry. Nested stacks is a useful feature that encapsulates logical functional areas which makes it easy to manage complex stacks. Similarly, changesets is another useful feature that allows you to inspect changes before applying them. However, CloudFormation is native to AWS. If your infrastructure is AWS-heavy, CloudFormation will serve a great purpose.
3) Database DevOps
DevOps is not just confined to development and operations. Database DevOps extends DevOps capabilities to databases as well, integrating development teams with database administrators (DBAs) such that database code is also included with the software code. As such, database changes can be efficiently monitored and added to the DevOps workflows.
In a traditional development environment, changes made to an application often require changes to be made to the corresponding database. Developers wait for DBAs to make changes to databases that are stored in SQL scripts. These changes have to be reviewed before deploying data to production. As the review is done at the later phase of the workflow, the delay impacts the overall agility and productivity of the project. Errors identified just before a release can be risky and costly as well.
Database DevOps introduces a version control system for database changes. The source control allows you to run builds anytime and roll back if needed at your pace. It also offers an audit trail.
In database DevOps, database workflows are also integrated into the CI/CD pipeline with automation incorporated wherever possible. When a database code change is detected, the system automatically triggers a build. As such, database teams can closely work with other teams on code changes using a well-defined process to improve productivity while reducing task switching.
However, continuous deployment is not easy with regard to databases. When a code change triggers a change to the database schema, it should be migrated to a new structure. You need the right tools to do so. Snowchange is a powerful DevOps database tool that helps you in this regard.
SnowChange is a powerful DevOps database tool developed by James Weakly in 2018 to manage Snowflake objects such as tables, stored procedures and views. Written in Python, Snowchange fits easily into the DevOps CI/CD pipeline as all popular CI/CD tools offer a hosted agent for Python. It is a lightweight tool that follows an imperative approach to DCM (Database migration, schema change and schema migration). It uses a snowchange change script that contains SQL statements defining the state of the database. By looping target databases, the tool applies new changes to the required databases.
Sqitch, Flyway and Liquibase are a few other options in the DevOps database stack.
DevOps is a blanket term that deals with managing an entire product lifecycle. However, it is important to optimize every phase of the DevOps workflow. Choosing the right tool stack for the right process is the key to fully leveraging DevOps.
Confused about various tools, processes and configurations. Not to worry anymore. CloudTern is here to help. As an experienced DevOps company, CloudTern helps you in designing and implementing the right tool stack for your DevOps projects.
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The wait for 5G has finally ended as the new technology is already making waves in the communication segment in recent times. Three important advantages of 5G networks are high-speed internet connections, lower latencies and accommodation of a wide variety of devices in the form of IoT, sensors, smart devices into the network. Though it was launched in 2019 in a few states in the US, it took a while to spread out to other regions. While the Covid-19 virus delayed 5G adoption to some extent, the complexity in migrating workloads to the new network is another reason for this slow start. Right from autonomous vehicles and cloud gaming to smart cities and AR/VR apps, the year 2022 is going to see 5G networks transforming the technology landscape across all industries.
DevOps and 5G Networks
5G technology is powered by software-defined networks running on standard commodity hardware that is inexpensive, disposable and widely available. As such, it can be virtualized and deployed from a central location. Using Network Functions Virtualization (NFV) technology, you can virtualize network functions and package them in containers, eliminating the need for special hardware. As such, you can easily build and deploy Virtual Network Functions (VNFs) using cost-effective commodity hardware. Each function can be developed as a service using the microservices architecture. As such, these services can be deployed using containers and managed with container orchestration tools.
With SDNs, NVFs and VNFs, you don’t have to worry about traditional CapEx costs for the expensive hardware. Instead, you can subscribe to a cloud service and host central servers in the cloud. You can install edge computing at the work location and connect the local systems with the cloud servers. With a high-speed network and low latency, 5G technology allows you to deliver an on-premise experience to users. To further optimize costs, you can implement serverless computing wherein the infrastructure is automatically provisioned when a function is in operation. Once the function is executed, the cloud resources are terminated. That way, you only pay when your application is running. AWS Lambda is a popular serverless computing solution offered by AWS.
DevOps enables you to build, deploy and manage code and configurations with increasing efficiency. Using DevOps CI/CD pipelines, developers can build and deploy code in small batches with automation incorporated across the pipeline. The code is automatically tested, secured and deployed with continuous feedback loops. The same principle can be applied to infrastructure management. By implementing the Infrastructure as Code (IaC) method, you can deploy and manage infrastructure provisioning using config files. With configuration code going through the CI/CD pipeline, it will be versioned and deployed with ease. It means you can revert to an earlier working version in case of a crash. Terraform and AWS CloudFormation are two popular IaC tools that help you efficiently manage infrastructure automation.
The communication segment involves strict SLAs. Moreover, the presence of heterogeneous networks often poses a challenge to move network components between different CSP environments. With DevOps automation and continuous delivery, CSPs can efficiently manage SLAs. With Docker containers, network components can be easily deployed and moved across a wide variety of environments. It also brings seamless coordination and communication between vendors and the operators. With 5G networks accommodating more than a million devices per square kilometre that can seamlessly communicate with each other, businesses have endless options to innovate operations and stay ahead of the competition. Combined with DevOps, 5G is poised to disrupt the business network landscape.
While DevOps started off slowly, it has changed gears now, rapidly transforming the business operations of every industry. When it comes to the Telecom industry, IT experts opined that DevOps adoption will be low compared to other verticals as telcos deal with physical servers, routers, load balancers, cables, switches and other network components. However, DevOps was able to make inroads into the Telecom industry as well.
VoIP, Cloud and 5G
VoIP and cloud computing solutions have taken the telecom industry to the next level. However, cloud computing also brought huge competition into the industry wherein mobile operators and Internet Service Providers (ISPs) had to look for value-added services implementing web services, HTTP/REST and webRTC protocols to sustain this competition. All these changes transformed the hardware-heavy infrastructure turns into a software-enabled environment, allowing administrators to manage it from a centralized location.
The arrival of the 5G technology has made a big difference too. While the earlier connectivity networks relied heavily on physical infrastructure, the new 5G technology is a predominantly software-defined network wherein configurations are delivered as software. The Network Functions Virtualization (VNF) technology virtualizes network hardware that can be deployed in containers using Virtual Network Functions (VNF) technology. Combining 5G and edge computing, telecom operators are now able to compete with web-scale companies such as Skype and WhatsApp.
Telecom Workloads Challenges
However, the IT workloads of the telecom vertical are unique and come with specific challenges. The Telecom industry involves complex workloads that require extensive infrastructure customization. For instance, the Network Functions Virtualization (NFV) technology converts various switches, routers, servers, load balancers, firewalls etc. into virtual network services, facilitating communication across the infrastructure. It brings several cloud servers as well as multiple app versions into the picture. Unlike regular IT workloads that comparatively operate on a fixed infrastructure environment, telecom IT network environments are dynamic and rapidly evolving. A notable challenge is performing functional testing on VNF network models wherein all 3GPP elements are required. Performing regression testing for every RF software update adds up to this challenge.
When it comes to deployments, companies are required to frequently release new versions or fix patches on live networks. You don’t have the luxury of performing planned maintenance anymore. With the lifecycle of software abstracted away from the workloads, gaining a comprehensive overview of the entire operations is a challenge.
DevOps for Telecom Industry
DevOps helps telecom companies solve most of these challenges. Firstly, businesses can separate each network function into a microservice and easily package it into containers using a containerization tool such as Docker. These containers can be automatically deployed and easily moved across different environments. Clusters of containers can be efficiently managed by container orchestration tools such as Kubernetes. The modular architecture allows you to move elements between various NFV environments. Using Infrastructure as Code (IaC), businesses can deploy and manage the infrastructure using config files.
In addition to infrastructure deployment and management, DevOps helps telcos easily manage application delivery CI/CD pipelines. It helps developers to develop cleaner and bug-free code in smaller units and frequently update the VNF environments using automation tools. The continuous feedback loops monitor the code performance and deliver feedback regularly. As such, businesses can automate operations, reduce CapEx and gain faster time to market while delivering highly available, scalable and resilient network services. It enables seamless coordination between various Communication Service Providers (CSPs) as well.
The telecom infrastructure is a tough nut to crack for DevOps. However, taking advantage of its robust ecosystem comprising Microservices, Edge Computing, Disaggregated Networks, Infrastructure as Code (IaC), Continuous Delivery, Containerization, Monitoring, Automation etc., DevOps helps telecom companies successfully undergo deep digital transformation while keeping their operations future-proof.
DevOps had a dream run in the year 2021 and is sure to continue it into 2022. According to ResearchandMarkets, the global DevOps market was estimated at $4.31 billion in 2020 and $5.11 billion in 2021. This value is expected to touch $12.21 billion in 2026, growing at a CAGR of 18.95% between 2021 and 2026.
DevOps is innovating at a rapid pace. As such, organizations should proactively monitor technology changes and reinvent IT strategies accordingly. Here are the top DevOps predictions for 2022.
1) Distributed Cloud Environments
After hybrid and multi-cloud environments, distributed cloud networks are rapidly gaining popularity in recent times. A distributed cloud environment hosts backend services on different cloud networks in different geolocations while offering a single pane to monitor and manage the entire infrastructure as single cloud deployment. It allows you to customize more-performing and responsive service delivery for specific apps while following regulations of local governments. Distributed clouds bring high resilience, prevent data losses and service disruptions as your apps keep running even when servers in one region crash. It means you gain 99.99% uptime. Edge computing can be considered as an extension to distributed cloud networks.
Distributed clouds offer amazing benefits to all industries. For instance, autonomous vehicles can monitor and process sensor data on-board while sending engine and traffic data to the central cloud. Similarly, OTT platforms can leverage ‘Intelligent Caching’ wherein content in multiple formats is cached at different CDNs while transcoding tasks are done at the central cloud. That way, a newly released popular series can be seamlessly streamed to multiple mobile devices in the same region in real-time.
2) Serverless Architecture
Serverless architecture is a cloud-native architectural pattern that enables organizations to build and run applications without worrying about the provisioning and management of server resources in the infrastructure. The cloud provider takes care of the allocation and management of server and machine resources on-demand. The serverless architecture delivers accelerated innovation as apps can be deployed faster and better. Apps can be decomposed with clear observability as independent services that are event-based. As such, organizations can reduce costs and focus more on delivering better UX.
Serverless computing is rapidly innovating. Function as a Service (FaaS) is a new trend based on the serverless architecture that eliminates the need for complex infrastructure to deploy and execute micro-services apps. Another growing trend is hybrid and multi-cloud deployments that deliver enhanced productivity and are cost-effective. Serverless on Kubernetes is another trend that helps organizations run apps everywhere where Kubernetes runs. Kubernetes simplifies the job of developers and operations teams by delivering matured solutions powered by the serverless model. Serverless IoT is another model that brings high scalability, faster time to market while reducing overhead and operational costs in data-driven environments. It is also changing the way how data is secured in serverless environments.
DevSecOps is a DevOps pattern that converts security into a shared responsibility across the application product lifecycle. Earlier, security was handled by an isolated team at the final stage of product development. However, in today’s DevOps era wherein apps are deployed in smaller cycles, security cannot wait for the end any longer. As such, DevSecOps integrates security and compliance into the CI/CD pipeline, making it everyone’s responsibility. The year 2022 is going to see more focus on shifting security towards the left of the CI/CD pipeline.
DevSecOps increases automation and policy-driven security protocols as QA teams perform automated testing to ensure that non-compliance and security vulnerabilities are efficiently combated across the product lifecycle. The design for failure philosophy is going to be reinvented as well.
4) AIOps and MLOps
Today, regardless of the size and nature, every organization is generating huge volumes of data every day. As such, traditional analytics solutions are inefficient in processing this data in real-time. For this reason, artificial intelligence and machine learning algorithms have become mainstream in recent times.
AI and ML data scientists normally work outside version control systems. Now, CI/CD and automatic infrastructure provisioning are applied to AIOps and MLOps as well. It means you can version your algorithms and identify how changes evolve and affect the environment. In case of an error, you can simply revert to an earlier version.
5) Infrastructure as Code (IaC)
Infrastructure as Code is another growing trend that will become mainstream in 2022. Infrastructure as Code (IaC) is a method of managing the complete IT infrastructure via configuration files. Since cloud-native architecture is becoming increasingly popular in recent times, IaC enables organizations to easily automate provisioning and management of IT resources on a cloud-native architecture by defining the runtime infrastructure in machine-readable files. IaC brings consistency in setup and configuration, enhances productivity, minimizes human errors, and increases operational efficiencies while optimizing costs.
GitOps is the new entrant in this space. Leveraging the IaC pattern and Git version control system, GitOps enables you to easily manage the underlying infrastructure as well as Kubernetes instances. When combined, organizations can build self-service and developer-centric infrastructure that offers speed, consistency and traceability.
DevOps was introduced between 2007 and 2008 as a revolutionary methodology that would be disrupting the IT development landscape. While DevOps was successful in changing the way how IT thinks and operates, it took a long time for companies to adopt this methodology. The reason for this slow adoption was because businesses took time to understand how DevOps works. While organizations are aggressively embracing this methodology in recent times, there are still some misconceptions that are acting as a barrier to DevOps implementation. Here are the top 10 myths about DevOps development.
1) DevOps is a Tool
The most popular myth about DevOps is that it is a tool or a product which is not true. DevOps is not a tool or a technology that can be purchased or subscribed to. It is a methodology that integrates development, operations, QA and security teams into a cross-functional team to seamlessly collaborate and work on software development projects. The system uses tools, processes and people to achieve this. For instance, continuous integration is achieved using CI servers such as Bamboo, Jenkins, Gitlab etc. while Docker and Kubernetes help in automatic deployment and management of the infrastructure.
2) DevOps is for the Web
DevOps became popular with SaaS-based organizations such as Netflix and Etsy creating an impression that DevOps is only for web companies. While it is true that DevOps favours web platforms, it is equally effective for all types of modern software delivery. While continuous delivery helps web companies to always offer up-to-date software, the same applies to native and non-web software too.
3) DevOps means CI/CD
While DevOps helps organizations achieve continuous delivery by building CI/CD pipelines, it is only a part of the DevOps methodology. DevOps is not confined to CI/CD but deals with the organization more comprehensively. In addition to tools and processes, DevOps brings a cultural shift across the organization by creating cross-functional teams that seamlessly collaborate and communicate across the product lifecycle. To fully leverage DevOps, businesses should equally focus on people, tools and processes.
4) DevOps Solves all Problems
It is a common misconception that when you use DevOps to build continuous delivery pipelines and automate processes, the system will take care of everything without any issues. First of all, you need to design the right DevOps strategy with the right tools for the right processes that are managed by the right people. In addition, to automating processes, you need to set up continuous feedback loops, analyse metrics and constantly update things. DevOps is not a magic wand that automatically sets everything right.
5) DevOps is for Developers and Operations Teams
DevOps stands for Development and Operations. While it started off a system that integrated these two teams to collaboratively work on a software development project, it has greatly evolved now. Today, DevOps cross-functional teams include people from QA, security, administrators, data engineers, analytics engineers and business management. It is interesting to note that members from sales, marketing, and tech support and customer service are also being incorporated into cross-functional teams as and where applicable.
6) DevOps is the End of Operations Teams
In an automated DevOps environment, developers can automatically deploy software to production environments using tools such as Jenkins, TeamCity, Docker, Kubernetes etc. However, it doesn’t mean that it is the end of the road for operations professionals. Actually, Ops teams can take advantage of Infrastructure as Code (IaC) tools to efficiently manage the infrastructure via code. DevOps teams are accountable for the entire lifecycle of the product and Ops teams have an important role to play here.
7) Operations Professionals Should Learn Programming
With infrastructure as code taking the center stage of the infrastructure management landscape, there is a misconception that operations professionals should learn programming languages. While it is true that you need a basic idea of scripting, you don’t need to have expert knowledge of programming languages such as Java or C#. For instance, Ruby is a popular IaC language that is easy to learn. So, Ops teams with basic scripting knowledge can easily pick up this system.
8) DevOps is only for Non-Regulated Industries
Often, people think that DevOps doesn’t work well with highly regulated industries, owing to strict compliance and security policies. DevOps serves a great purpose for regulated industries as well. With DevOps, compliance becomes easy as you can store audit trails of all automated processes. It means business processes are always audit-ready.
9) DevOps is Cloud-based
Often, people believe that DevOps is always deployed in the cloud and some people use the term ‘cloud’ interchangeably with DevOps. DevOps indeed brings dynamic infrastructure resources into the picture. However, it doesn’t mean that DevOps always requires a cloud infrastructure. If you can dynamically test and deploy code, then DevOps works for you.
10) DevOps replaces Agile
A popular myth about DevOps is that it replaces agile which is not true. In fact, DevOps enables agile practices by incorporating continuous integration, continuous testing, continuous deployment and continuous monitoring. So, it actually complements agile software development.
The key to fully leveraging DevOps is choosing the right DevOps strategy. CloudTern is here to help!
DevOps started off as a methodology that integrates Developers and Operations teams to work in tandem in software development projects. It facilitates seamless coordination and communication between teams, reduces time from idea to market and significantly improves operational efficiencies while optimizing costs. Today, DevOps has rapidly evolved to include several other entities of IT systems. A new addition is Business intelligence.
DevOps jelled well with Big Data as both methodologies are contemporary and complement each other in managing of massive volumes of live data moving between development and production that is maintained relevant via seamless coordination between teams. When it comes to business intelligence, data warehousing and analytics are two important components that need to be managed. As BI deals with batches of data, it doesn’t easily integrate with the DevOps environment by default.
Managing Data Warehousing with DevOps
A data warehouse is a central data repository that collects data from various disparate data sources in and outside the organization and hosts them in a central location allowing authorized people and reporting and analytics tools to access it from any location. Managing a robust and sophisticated data warehouse is a challenge as multiple stakeholders are involved in making a change which makes deployments rather slow and time-consuming. Implementing DevOps here can be a revolutionary thing as you can combine data administration teams and data engineering teams to collaborate on data projects. While a data engineer informs potential features that are being introduced to the system, the data administrator can envisage production challenges and make changes accordingly. With cross-functional teams and automated testing in place, production issues can be eliminated. Together, they can build a powerful automation pipeline that comprises data source analysis, testing, documentation, deployment etc.
However, introducing DevOps for data warehouse management is not a cakewalk. For instance, you cannot simply backup data and revert to the backup as and when required. When you revert to a last week’s backup, what about the changes made to the data by several applications?
DevOps for Analytics
The analytics industry is going through a transformation as well. Contrary to the traditional analytics environment that uses a single business intelligence solution for all IT needs, modern businesses implement multiple BI tools for different analytical purposes. The complexity is that all these BI tools share data between them and there is no central management of BI tools. Another issue is that data scientists design models and algorithms for specific data sets to gain deeper insights and offer predictions. However, when these data sets are deployed to the production environment, they serve a temporary purpose. As data sets outgrow, they become irrelevant which means continuous monitoring and improvement is required. The rate at which the data drifting happens is enormous and traditional analytics solutions are inefficient to manage this speed and diversity. This is where DevOps comes to the rescue.
DevOps helps businesses integrate data flow designs and operations to automate and monitor data enabling them to deliver better applications faster. Automation enables organizations to build high performing and reliable build-deploy iterative data pipelines for improving data quality, accelerate delivery and reduce labor and operational costs. Monitoring data for health, speed and consumption-ready status enable organizations to reduce blindness and eliminate performance issues. It means a reliable feedback loop is created that covers data health, privacy and data delivery for ensuring smooth flow of operations for planned as well as unexpected changes.
The Bottom Line
Bringing DevOps into the BI realm is not an easy task as BI environments are not suitably designed for DevOps. However, businesses are now exploring this option. Bringing DevOps into the BI segment gives situational awareness to businesses as they can make informed decisions when they gain insights into relevant data added from multiple sources. Moreover, it brings great collaboration between teams, allows better integration between different application layers while helping businesses to explore and quickly tap into new markets. Most importantly, it makes your business future-proof.