Era Software announced the private beta version of EraStreams, a no-code data pipeline that lets users integrate, transform, and route observability data to EraSearch, the company’s petabyte-scale log management platform, and third-party monitoring tools.
Era Software is broadening the scope of its log management solution and fitting into more of the observability stack. With a time series database and object storage under the hood, the company’s approach to observability data management resolves scale, performance, and cost issues associated with running applications on modern architectures, including cloud, containers, and microservices.
EraStreams complements EraSearch to optimise cost and performance and integrates into existing DevOps workflows and tools to help teams manage observability costs and improve troubleshooting effectiveness. As a result, IT and security teams can continue to use monitoring tools they rely on while controlling the volume of data that gets routed to these tools to optimise data usage and cost-efficiency. Teams also can route any logs to EraSearch for low-cost storage and fast, petabyte-scale query.
“Our vision is to be the observability data management choice for organisations dealing with massive volumes of observability data. The unveiling of EraStreams today advances this vision with a data pipeline to help you manage observability costs and improve troubleshooting effectiveness. In addition, it gives you real-time insights into application and system performance and adds another component to our scalable, cost-effective observability data management,” said Todd Persen, Co-Founder and Chief Executive Officer, Era Software.
EraStreams better handles failure modes and pipeline changes to minimise data loss with dynamic backpressure management and reconfigurations. In addition, EraStreams provides a powerful set of features that offer multiple ways to reduce observability costs. When used with EraSearch, EraStreams reduces the total cost of ownership for existing log management solutions while preserving historical information in EraSearch for low-cost object storage and fast search and query.
