Operations | Monitoring | ITSM | DevOps | Cloud

How do you ensure best coding practices are being adopted and reinforce this approach in your entire pipeline? In this video we show you how the same best practices are unified in the Code Analysis functionality offered by SQL Prompt, SQL Change Automation and SQL Monitor to ensure your team are making the best possible changes.

Do traditional on-prem observability techniques translate to the cloud? Many big data enterprises lack observability and thus struggle to manage and understand unprecedented amounts of data in the cloud. A monitoring solution may alert to a problem, but it can’t pinpoint the issue or quickly get to the root cause.

The promise of autoscaling is that workloads receive exactly the cloud computational resources they require at any given time, and you only pay for the server resources you need, when you need them.

Monitoring big data cloud performance in the cloud with unified visibility across the entire ecosystem is critical to the success of any cloud deployment. In both the data center and cloud deployments, a proliferation of diverse performance solutions and microservice applications across infrastructures and networks can severely complicate cluster performance management. Hidden network dependencies and the complexity of managing many different solutions can negatively impact the application experience for both internal and external users.

Big data with cloud computing is a powerful combination that can transform your organization, process, and analyze your big data faster, and improve your products and business with actionable insights. Bringing your big data cluster to the cloud presents huge opportunities, but there are some challenges that need to be overcome. Is your organization really ready for the complexity of managing big data analytics in the cloud?