Log Analytics Makes Cloud Operations Smarter

Enterprises walk a knife edge when it comes to digital transformation. They must scale their operations on the cloud, but somehow minimize complexity and disruptions.

The discipline of cloud operations (CloudOps) aims to strike the right balance by intelligently provisioning resources, utilizing capacity, and mitigating issues-all with the help of cloud log analytics.

DBTA held a webinar with Thomas Hazel, CTO and founder, ChaosSearch and Kevin Petrie, VP of research, Eckerson Group who discussed the role of log analytics in CloudOps, and the requirements, challenges, and benefits of log analytics for CloudOps.

Despite the hype, cloud computing makes IT more complicated than ever, Petrie said. Systems persist on premises, thanks to technical debt, data gravity, and sovereignty rules.

Cloud compute costs real money. You still need to manage applications, govern data, and connect back to on-prem system.

CloudOps encapsulates the processes and tools you need to achieve IT stability and agility on cloud platforms, according to Petrie.

Stability and agility requirements include:

  • Applying ITOps methodology to the cloud
  • Configuring resources, utilizing capacity, monitoring and responding to issues
  • Meet SLAs, support chargeback, and assist compliance
  • Apply DevOps methodology to the cloud
  • Continuously deliver applications and updates to users
  • Address urgent market needs, innovate, and make competitive enhancements

CloudOps needs deep knowledge of cloud components, that’s where log analytics comes in, Petrie said. Logs capture events such as user actions, application tasks, and compute errors. Log analytics means to ingest, transform, search, and query logs. You identify patterns, anomalies, and trends, and derive metrics to describe those trends.

ChaosSearch is a smarter and more cost effective way to implement these strategies, according to Hazel. ChaosSearch’s patented indexing technology activates your cloud data, rendering it fully searchable and enabling analytics at scale with massive reductions of time, cost, and complexity.

An archived on-demand replay of this webinar is available here.