Operations | Monitoring | ITSM | DevOps | Cloud

In Part 1 of this series, we looked at the key EFS metrics you should monitor, and in Part 2 we showed you how you can use tools from AWS and Linux to collect and alert on EFS metrics and logs. Monitoring EFS in isolation, however, can lead to visibility gaps as you try to understand the full context of your application’s health and performance.

A look at outages and disruptions to the IT systems that power the Olympics, from 1996 to today.

As the adoption to cloud expand, subscribing and provisioning resources increases day by day. Enterprises have multiple strategies to implement their cloud deployments: single cloud, private cloud, multi-cloud, or hybrid cloud. There is a need to analyse and assess on regular basis to keep a watch on the usage to ensure expenditure on the cloud resources are efficient and there is no wastage. There are various possibilities but will need some level of technical competence and regular maintenance.

In any integration solution, when many Azure services come together to communicate with each other, there is a need for the organizations to build an end-to-end traceability/monitoring solution that can be used by the business users and IT support. Perform end-to-end message tracking and capturing necessary data on business process flow across Azure resources and hybrid integrations. Consider an organisation that has a well-defined Employee Onboarding process.

As of August 5, 2021, JFrog will require newly created free JFrog cloud subscription users to provide valid credit or debit card information in order to activate Pipelines CI/CD. In the months since offering Pipelines CI/CD as part of a free JFrog cloud subscription, we have unfortunately experienced a rapid growth in abuse of the free compute resources from some accounts.

Data has gone from scarce, expensive, and hard to find and collect to rich and cheap, hard to process and understand with the digital age. In data science solutions, traditional software was used to capture, store, understand and analyze, but not all verticals of data science are essential for individuals and businesses. So Data visualization comes into play to make your tasks easy.

When you migrate workloads from on-premise infrastructure into a public cloud, you can improve the performance, reliability, and security of your application, and you might also lower your costs.

From containerized workloads to microservice architectures, developers are rapidly adopting new technology to scale their products at unprecedented rates. To manage these complex deployments, many teams are increasingly moving their applications to third party–managed services and infrastructure, trading full-stack visibility for simplified operations.