Adoption of AWS Lambda functions in cloud-native applications has increased exponentially over the past few years. Serverless functions, such as the AWS Lambda service, provide a high level of abstraction from the underlying infrastructure and orchestration, given these tasks are managed by the cloud provider. Software development teams can then focus on the implementation of business and application logic.
As more organizations adopt cloud-native technologies and microservices-based architectures, application troubleshooting is becoming increasingly complex. With so many moving parts in an environment that is both dynamic and distributed, it is difficult to get the full picture. Yet complete visibility is crucial in order to find and fix issues quickly — especially ones that impact the bottom line.
Elastic Enterprise Search 8.2 introduces new ways to ingest, search, and monitor data, giving developers the productivity benefits of using out-of-the-box capabilities along with the power and flexibility inherent in Elastic Stack tools. Operators also gain even more transparency for managing search experiences and observing search performance. For a visual walkthrough of some of the key capabilities in 8.2, check out the latest installment of What’s new in Enterprise Search on YouTube.
Let's start with the bottom line: When we upgraded to Elasticsearch 7.15 last year, our internal observability clusters saw a reduction in inter-node traffic from 464TB to 204.5TB per day. We monitored this reduction through subsequent upgrades and noticed its impact on our data transfer and storage costs. So here it is: upgrading saved Elastic $3,500 per day, or approximately $100,000 a month, or $1.2 million annually.
