DevOps is an attempt to scale technology with humans but AIOps is the ultimate answer.
In today’s world, where so many essential business tasks have become digitized, IT teams must deal with constant change while ensuring zero downtime.
The irony is that, although IT has become business-critical, the productivity and agility of the people building and supporting the customer experiences has plummeted. This has serious consequences for businesses. When your apps and services malfunction, you lose customers and revenue drops. When IT teams focus mostly on fixing emergencies, agility suffers and innovation shrinks. You need seamless operations in order to grow, compete and thrive.
Historically, IT teams grew along with technology, beginning with the mainframe through distributed computing. But, the advent of virtual computing led to a world of microservices and ephemeral logic. Now companies simply generate too much data for humans to monitor and understand manually and with legacy tools.
This opened the floodgates for an AI-led operations evolution, known as Artificial Intelligence for IT Operations (AIOps). By streamlining and automating IT monitoring, AIOps has helped IT Ops teams regain control over IT environments, quickly detect and repair problems, and prevent outages.
DevOps: Back to the Future?
However, there’s recently been a shift in technology operations to once again attempt to scale technology with humans. The DevOps movement has placed the ownership, support and success of their services on the developers that write the code. This has decentralized technology operations teams that primarily operated with little context and unclear escalation paths, creating several smaller teams of DevOps engineers.
DevOps teams work together, each on their own microservice, toward the company’s desired customer experience and business goals. Depending on the operations model, there can also be a dedicated site reliability engineering (SRE) team or individuals on the DevOps team with the primary SRE role of monitoring observability data to discover potential issues. In this scenario, SREs feed the insights they uncover back into the development cycle to correct and strengthen the reliability and scalability of the DevOps teams’ services.
But, as incidents occur in real-time, the challenge remains with SREs and DevOps teams to achieve insights and awareness across their applications, infrastructure and, ultimately, business services. To understand where incidents are occurring and what impact they’re having on the services and customers, it’s necessary to surface important events from the noise, understand the relationships between alerts and obtain the context needed to engage the right teams and people.
This leads to another challenge: Getting the right people to respond and resolve incidents before there’s any business impact. Each DevOps team has its own responsibilities and tools. Often, DevOps teams don’t communicate except through their APIs. When incidents occur that need immediate attention from multiple people from multiple geographically-dispersed teams, how do you contact them and get them to collaborate, considering they have complex and different on-call schedules and escalation processes?
As companies continue to transform with a customer experience focus and a digital-first mentality, they realize the seriousness of these challenges, the magnitude of their monitoring data and its negative effect on their business. Part of transforming their business is transforming their technology operations: Enter AIOps with the light to shine on DevOps processes, leading to a manageable, efficient and profitable future.
What AIOps Brings to DevOps Teams
AIOps provides a unique solution to address operational challenges and cover every aspect of your service assurance strategy and business.
Bottom line: You need to free people to focus on mission-critical tasks and empower them to build better services for better customer experiences—not scale them along with technology in an attempt to operate it.
AIOps allows you to scale by integrating with the tools and infrastructure you’ve invested in over the years and by adding critical layers of AIOps (intelligence) throughout. By applying patented AI and machine learning algorithms to your observability and monitoring data, AIOps learns your environment’s normal behaviors and generates alerts accordingly. This must be done at the edge, close to where digital services produce vast amounts of data.
Based on the anomalies generated both locally and environmentally, AIOps will then surface and correlate important alerts from all sources into actionable, contextual insights. A true, comprehensive AIOps solution also identifies root causes and impacts, and prescribes potential solutions based on previous resolution steps and feedback. This all occurs in a virtual workspace, where team members can collaborate, visualize and provide feedback.
AIOps notifies and empowers the right people to take the right action. It simplifies and understands complex team structures, engagement methods, on-call schedules and escalation paths, ensuring the right people are engaged and collaborate, even when they’re located around the globe.
When a situation or incident is surfaced, it is sent to users in real-time. Based on the insights derived from the underlying data and machine learning applied, AIOps knows the exact teams and people that need to take action, and the ones that need to be informed. These users have the context they need to respond, share a consistent view and stay in sync throughout the lifecycle of the incident. Once the incident is resolved, a streamlined post-mortem speeds up future response, by using similar incidents and predictive analysis to spot repetitive and future problems.
AIOps: A Key Ingredient for Effective DevOps
The only way to scale with the technology being created in today’s and tomorrow’s world by DevOps teams is with AI. It frees humans to focus on creating and improving the customer experience that drives maximum profitability for your business.