Operations | Monitoring | ITSM | DevOps | Cloud

With companies expecting software products to handle constantly increasing volumes of requests and network bandwidth use, apps must be primed for scale. If you need resilient, resource-conserving systems with rapid delivery, it is time to design a distributed system. To successfully architect a heterogeneous, secure, fault-tolerant, and efficient distributed system, you need conscientiousness and some level of experience.

Memory (or RAM, short for random-access memory) is a critical computing resource that stores temporary data on a system. Memory is a finite resource, and the amount of memory available determines the number and complexity of processes that can run on the system. Running out of RAM can cause significant problems such as system-wide lockups, terminated processes, and increased disk activity. Understanding how and when these issues can happen is vital to creating stable and resilient systems.

As software applications grow in scale and complexity, the surface areas for security vulnerabilities and exploits grow with it. Modern development practices include large amounts of code reuse. First, in the form of language-specific standard libraries such as the C++ STL, the Golang standard library, and Microsoft.NET. Second, in the form of open-source libraries found on places like Github. Much of this code is built using other libraries, introducing a web of dependencies into modern software.

In this episode Jason is joined by John Martinez, Director of Cloud R&D at Palo Alto Networks, to talk about the FinOps Foundation and the vast range of optimization opportunities to reduce spend in the cloud. John comes in with some extremely useful insights into how FinOps is laid out and their use of a “crawl, walk, run approach.” John and Jason discuss multi cloud and go into the specifics on the costs associated with multi cloud as well the security changes that will come with.

As you scale microservices adoption in your organization, the chances are high that you are managing multiple clusters, different environments, teams, providers, and different applications, each with its own set of requirements. As complexity increases, the question is: How do you scale policies without scaling complexity and the risk of your applications getting exposed?

In a recent survey of hybrid cloud decision makers, we uncovered a disconcerting trend. The vast majority of respondents reported that they are confident in their existing tools and capabilities for a whole host of activities necessary to manage cloud performance and spend … and yet they don’t have many of the tools that are actually needed to perform those tasks.