In the domain of cyber threat response, there’s a critical resource that every organization is desperately seeking to maximize: time. It’s not like today’s DevOps teams aren’t already ruthlessly focused on optimizing their work to unlock the greater potential of their human talent. Ensuring your organization to identify and address production issues faster – and increase focus on innovation – is the primary reason why Logz.io and its observability platform exist.
With the recent release of Loki 2.4 and Grafana Enterprise Logs 1.2, we’re excited to introduce a new deployment architecture. Previously, if you wanted to scale a Loki installation, your options were: 1) run multiple instances of a single binary (not recommended!), or 2) run Loki as microservices. The first option was easy, but it led to brittle environments where a heavy query load could take down data ingestion and problems were often difficult to debug.
AIOps is an approach to managing the exponential growth of IT operations and the complexity of new technology through the application of artificial intelligence (AI). IT infrastructure increasingly relies on complicated deployments, multi-cloud architectures, and huge amounts of data. Traditionally, the tech industry responds to complexity by applying extra brainpower to the problem, bringing in more engineers, developers, and management.