There is a new trend going around, one which has been hard to miss: Artificial Intelligence for IT Operations (AIOps). Gartner predicts that DevOps teams that leverage AIOps platforms to deploy, monitor and support applications will increase delivery cadence by 20%. AIOps technology is rapidly evolving and is relatively new, so there are a lot of variations in this space. In this post we will discuss use cases of how AIOps systems help you to accelerate the velocity of your software delivery pipeline.
What is AIOps?
AIOps represent the evolving and expanded use of technologies previously categorised as IT operations analytics (ITOA) and is the intersection of Artificial Intelligence and Operations. AIOps systems are using AI to support several IT functions such as developing, releasing, monitoring and supporting applications. Gartner describes AIOps as “combining big data and machine learning to automate IT operations processes.”
Why do we need AIOps?
The software industry’s transition into complex systems is accelerating. Almost each and every organization is using (or planning to use) microservices, Kubernetes and cloud. The humans designing, building, and operating these distributed architectures are no longer capable of understanding how all of the pieces fit together and making the right decisions. Instead of fighting the complexity, we are learning to navigate it.
That’s where AIOps comes in and is able to help us.
At Vamp we’re talking to a lot of organizations who are facing issues related to their development pipelines. It all boils down to the following technical issues and its impact on the business:
- Technical issue: you’ve moved to microservices, but your delivery pipeline is still monolithic. Business impact: not reaping the benefits of microservices and cloud-native technologies. Output (features) of your teams goes down. Your boss is starting to wonder why you’ve moved to microservices.
- Technical issue: releasing software to production is usually thought of as the moment someone in a technical role deploys a new version of code to production. Business impact: missed opportunity to optimize impact of the release on customer satisfaction, platform performance and revenue. Releasing is the only part that directly impacts business value.
- Technical issue: scripted release strategies (blue/green, canary) take a lot of time to create and maintain + it doesn’t scale. Business impact: wasted time (toil). Your teams are spending more time on maintaining instead of innovation.
- Technical issue: hand-holding software releases and manually validating the performance of new production software. Business impact: again, wasted time (toil) and your teams are reactive to issues instead of proactive.
- Technical issue: troubleshooting issues is hard due to a lot of moving pieces. Rollback of software takes too long. Business impact: downtime, missed revenue, unavailable services and impacted Net Promotor Score and unhappy customers.
- Technical issue: teams have a hard time defining Kubernetes runtime scale settings and thus over-dimension. Business impact: unnecessary rising cloud costs. Unhappy CFO.
👆🏽 I bet you recognize (and face) at least three of these challenges and issues. No worries, AIOps is here to help. Step by step. Here are 3 value props of how AIOps can help you out and accelerate your delivery pipeline.
The Value of AIOps for Your Software Delivery Pipeline
1. Reducing toil with automation (or achieve more with less)
Toil, as defined by Google, is work related to running a production service that is repetitive, manual, automatable, and that scales linearly as a product/service/application grows. With software delivery, there’s (unfortunately) a lot of toil involved. Teams are spending time on scripting and maintaining release strategies (such as a canary release). Another form of toil is manually validating new software in production. Engineers and operators are baby-sitting their releases and spending hours toggling between infra monitoring, APM and log analytics tools to make sure their new software is performing well.
AIOps systems help to automate these toil-related activities/decisions and acts as an autonomous system that continuously scans for issues and improvements. AIOps technology (such as Vamp) is also able to perform an automated rollback when things tend to go wrong. With AIOps, teams can finally work in a stress-free environment and focus on innovation and revenue-generating features.
2. Speed up Time-To-Market, Reduce Time-To-Feedback
Without good feedback loops from production environments, IT teams tend to make changes too much too fast — increasing their chances of issues, failures or even downtime. Identically, many teams and IT managers are overly cautious and risk-averse unless there is constant feedback through end-user analytics or monitoring. Continuous feedback (based on IT and business metrics) during and after software releases mitigates these problems and enables change to be delivered successfully and quickly.
3. Optimize cloud costs and application performance
Many enterprises are adopting Kubernetes, because it has the power to make applications flexible, as well as cheaper to deploy. However, this promise is offset by its complexity – it offers operators endless options for tuning application performance in production. That makes it impossible to reliably deploy applications and achieve consistently high performance manually. As a result, operators default to over-provisioning to ensure they get the performance they need. This means that with operational agility comes increased operational costs.
AIOps systems help with finding the right balance between application performance and cloud costs. Based on real-time data that’a available across the enterprise it calculates the precise operational capacity needed to run an individual service, while safeguarding application performance. But it doesn’t stop there. It not just provides recommendations, but is also able to actually adjust the settings on the fly.
Vamp is your partner towards AIOps
The goal of AIOps is to build systems that are autonomous and not just automated. Here at Vamp we're building an AIOps platform for release orchestration that makes software releases self-driving and self-healing. Our platform has a lot of out-of-the-box building blocks that helps IT organizations to start moving towards intelligent and autonomous release automation. It's our mission to help IT teams navigating the complexity. If you're interested to learn how you can start with AIOps and how it can help to accelerate your delivery pipeline, feel free to request a guided tour and talk to one of our technical experts.