Two steps to effective cloud operations  

Welcome, cloud operations

Make your cloud infrastructure and applications more reliable with site reliability engineering (SRE).

Many enterprises have embarked on the cloud journey and moved their workloads to public or hybrid cloud. 

As they migrate their business applications to the cloud, enterprises are also exploring how traditional operations teams that monitor IT infrastructure can be utilized to improve end-user experience and infrastructure life-cycle management. They are also realizing that effective coordination between developers, test engineers, and security teams is a must for better problem resolution. So, what can be done to ensure all this and get maximum value from cloud operations? SRE, a new operating model that uses software engineering principles to optimize the reliability of applications and infrastructure, is key. The SRE team can also collaborate with DevOps, ITOps, and development teams; and reduce friction between these teams to improve the reliability of an IT environment.

Ensuring site reliability

SRE supports cloud operations to maintain the performance and quality of services provided to end users.

From automating cloud operations to building self-service tools for auto provisioning of cloud resources, SRE helps in running an efficient cloud environment. With faster trouble shooting and automated resolution of repetitive service requests and incidents, it saves time for developers to focus on development-related activities. Companies adopting this new operating model are improving resiliency and time-to-market by 20% or more.

By leveraging SRE in their cloud operations, enterprises can boost infrastructure security and reduce application failures by ensuring highly available and scalable infrastructure. That’s not all. They can monitor application performance, apply quick fixes to eliminate performance bottlenecks, and enable faster recovery of services.

Simplifying cloud operations

Leverage artificial intelligence in IT operations (AIOps) to identify and solve issues in cloud operations.

Cloud’s distributed architecture and increasing complexity make it a herculean task for the operations team to achieve service reliability with specific SLAs. Simplifying cloud operations with AIOps can make all the difference. Here's how: 

• AIOps reduce manual efforts and identifies, analyzes, and remediates events or issues in cloud environments faster. 

• With AIOps predictions, the cloud operations team can proactively monitor and take preventive actions to avoid incidents or alerts. 

• They can make the most of AIOps predictions for cost optimization and insights into cost-saving opportunities.  

• With its automation and machine learning capabilities, AIOps helps reduce human errors. 

• AIOps collects distributed data into a common platform to perform analysis and provide insights and improves the time taken for root cause analysis through event correlation.

What’s more, AIOps enables observability with dashboard-based performance analysis. Observability is the ability to measure the current state of a system based on the data it generates such as logs, metrics, and traces. By leveraging AIOps, enterprises can achieve improved observability on its applications, remediating problems faster and increasing reliability.

Another area where AIOps helps is in optimizing costs. It does so by reducing human interventions through automation and repetitive issues and automation of anomaly detection and root cause analysis. And using insights from analysis of utilization metrics, it also plays a major role in measuring the performance of cloud resources and recommending right-sizing of resources to reduce costs.