But there are core differences between operating containers , whether on premises or in the cloud , and monitoring traditional application workloads in production . For example :
• Containers interact in production in complex and distributed ways , and you need the ability to monitor each container instance , no matter if it ’ s replicated or not , as well as any external resources that it accesses .
• Because you ’ re dealing with container images based upon container images , you need to understand the coupling there as well .
• Security monitoring needs to be ongoing ; you can ’ t scan-and-go as with traditional applications .
• You need to understand how to monitor microservices as well , which typically takes a more fine-grained approach .
You must consider resiliency , which encompasses business continuity and disaster recovery ops . This typically involves creation of an active / active approach , where a replica of the container-based system in production is standing by and ready to go . Given the portability advantage of containers , using a different public cloud provider is a possibility as well .
In leveraging best practices , processing , and tooling around DevOps , you need to consider patches and upgrades to the production environment as they flow from the developers to ops . You will need tools that provide continuous integration , continuous testing , and continuous deployment , while remembering that tools are still emerging for the special needs of containers .
48 | THE DOPPLER | FALL 2017