A help desk is a group, department, or external service that users contact for assistance through various channels.
Observability tools have traditionally focused on capturing and analyzing log data to improve application performance monitoring and security. Data observability turns the focus back on the data to improve data quality, tune data infrastructure and identify problems in data engineering pipelines and processes. “Data analysts and business users are the primary consumers of this data,” said Steven Zhang, director of engineering at Hippo Insurance.
Welcome back! In the previous blog, we discussed with our panelists Carlos Casanova, Forrester principal analyst, and Gowrisankar Chinnayan, who heads product management at ManageEngine, why organizations should adopt AIOps, and the challenges they face. Let’s start by acknowledging the increasing interest in AI. More enterprises are adopting AI-based solutions as they discover how AI can help manage IT operations.
When it comes to creating new Pods from a ReplicationController or ReplicaSet, ServiceAccounts for namespaces, or even new EndPoints for a Service, kube-controller-manager is the one responsible for carrying out these tasks. Monitoring the Kubernetes controller manager is fundamental to ensure the proper operation of your Kubernetes cluster. If you are in your cloud-native journey, running your workloads on top of Kubernetes, don’t miss the kube-controller-manager observability.
Repatriation in cloud computing refers to moving workloads from the public cloud to on-premise infrastructure. Sarah Wang and Martin Casado from Andreessen Horowitz have written one of the most popular articles about repatriation: they explain the motivation with the significant cost savings possible. For software-based businesses, public cloud spend can rise to 50% of the cost of revenue (COR). Reducing these costs has the potential for significant margin increases.
As an observability provider, we are always confronted with our clients’ goal for faster resolution of problems and better overall performance of their systems. By working on large-scale projects at Logz.io, I see the same main challenge coming up for all: extracting valuable insights from huge volumes of data generated by modern systems and applications.
We’re excited to announce significant improvements to our Archive+Restore capabilities – which enables low-cost long term log storage in AWS S3 or Azure Blob, while providing access to ingest those logs into Logz.io at any time. The first enhancement is Power Search, which will make it faster to restore logs from archived log data in AWS S3 (and soon for Azure Blob) in our Open 360™ platform.
