Ray is an open source compute framework that simplifies the scaling of AI and Python workloads for on-premise and cloud clusters. Ray integrates with popular libraries, data stores, and tools within the machine learning (ML) ecosystem, including Scikit-learn, PyTorch, and TensorFlow. This gives developers the flexibility to scale complex AI applications without making changes to their existing workflows or AI stack.
Throughout 2023, one thing has become abundantly clear: regardless of an organization’s size or industry, incidents are inevitable. Recently across the APAC region, we’ve seen numerous regulatory bodies clamp down on large companies who are failing to provide acceptable service, with some handing out quite severe penalties. For many, the cost of an incident is no longer just lost revenue and customer trust, but financial penalties and business restrictions.
Effective monitoring and observability tools are critical for modern enterprises. Daily operations, digital transformation, moving to a cloud-native architecture, and an ever-evolving tech stack all require ITOps, DevOps, and SRE teams to monitor increasingly complex systems. So what happens if your applications suddenly cease to function? Every moment of downtime translates to lost income, decreased customer satisfaction, and harm to your company’s reputation.
Gartner’s IT Infrastructure, Operations & Cloud Strategies Conference (IOCS) is an annual event that attracts ITOps, SRE, and DevOps leaders from around the world. As Gartner explains, IOCS “brings the world’s technology leaders together to hear top trends, find objective answers, and explore topic coverage in addition to best practices. Gain the insights and guidance to create an effective pathway to the future and network with your peers.”
The two key pillars of building reliable applications are: testing and monitoring. With testing, you can verify that each pull request works before it’s merged and deployed to production. Just testing isn’t enough, though. You also need to make sure that the application continues to work on production. Database rollovers, third-party outages, and unexpected spikes in traffic can all cause issues that need to be detected.