Full Stack Observability use cases

Business Use Cases

Full Stack Observability is all about collecting any possible data from the applications running your digital services (i.e. business KPI) and from the infrastructure and cloud resources supporting them (i.e. the telemetry), including potentially also IoT, robots or whatever device involved in the process.

And then correlating those data to create an actionable insight, so that you have full control of your business processes end-to-end and you do better than your competitors (faster, more reliable, more appealing processes and services).  

The FSO value proposition is not only related to technology (the infrastructure that you can monitor and the metrics you can read). It is a business value proposition, because observability has an immediate impact on the business outcomes.

Associating business processes, and digital services supporting those, with the health state of the infrastructure gives the Operations teams an immediate and objective measure of the value - or the troubles - that IT provides to their internal clients, that are the lines of business (LOB). And LOB managers can enjoy dedicated dashboards that show how the business is doing, highlighting all the key performance indicators (KPI) that are relevant for each persona in the organization.  

If there is any slowdown in the business, they see it instantly and can eventually relate it to a technical problem, or maybe to the release of a new version of a software application, or to the launch of a new marketing campaign. The outcome of any action and of any incident is connected to the business with... no latency. The same visibility is also useful when the business shows a better performance than the day before. You can relate outcomes to actions and events.

So, before speaking about the technology that supports the Full Stack Observability, let's discuss about the use cases and their impact.

We can group the use cases in three categories: Observe, Secure and Optimize (referred to your end-to-end business architecture).

In the Observe category, we have 4 fundamental use cases:

- Hybrid application monitoring

This refers to every application running on Virtual Machines, in any combination of your Data Center and Public Clouds, or on bare metal servers.

You can relate the business KPI (users served, processes completed, amount of money, etc.) to the health state of the software applications and the infrastructure. You can identify the root cause of any problem and relate it to the business transactions (= user navigation for a specific process) that are affected.

- Cloud native application monitoring

Same as the previous use case, but referred to applications designed based on cloud native patterns (e.g. microservices architecture) that run on Kubernetes or Openshift. Regardless it's on premises, in cloud, or in a hybrid scenario. Traditional APM solutions were not so strong on this use case, because they were designed for older architectures.

- Customer digital experience monitoring

Here the focus is on the experience from the end user perspective, that is affected by the performance of both the applications and the infrastructure, but also - and mostly - by the network. Network problems can eventually affect the response time and the reliability of the service because the end user needs to reach the end point where the application is run (generally a web server), the front end needs to communicate with the application components distributed everywhere, and these may be invoking remote API exposed by a business partner (e.g. a payment gateway or any B2B service).

- Application dependency monitoring

In this use case you want to assure the performance of managed and unmanaged (third-party) application services and APIs, including performance over Internet and cloud networks to reach those services. Visibility of network performance and availability, including both public networks and yours, is critical to resolve issues and to push service providers to respect the SLA of the contract.

In the Secure category, we can discuss the Business Risk Observability use case:

- Application security

Reduce business risk by actively identifying and blocking against vulnerabilities found in application runtimes in production. Associate vulnerabilities with the likelihood that they are exploited in your specific context, so that you can prioritize the suggested remediation actions based on the business impact (shown by the association of vulnerabilities with Business Transactions).

In the Optimize category, we have the following use cases:

- Hybrid cost optimization

Lower costs by only paying for what you need in public cloud and by safely increasing utilization of on—premises assets.

- Application resource optimization

Improve and assure application performance by taking the guesswork out of resource allocation for workloads on—premises and in the public cloud.

Observability and network intelligence coming together

The use cases listed above goes beyond the scope of traditional APM solutions (Application Performance Monitoring) because they require to extend the visibility to every segment of the network. This picture shows an example of possible issues that can affect the end user experience, and need to be isolated and remediated to make sure the user is happy.

That is generally difficult, and requires a number of subject matter experts in different domains, and a number of tools. Very few vendors can offer all the complementary solutions that give you visibility on all aspects of the problem. And, of course, they are not integrated (vertical, siloed monitoring). 

Data-driven bi-directional integration 

The Full Stack Observability solution from Cisco, instead, covers all the angles and - in addition - it does so in a integrated fashion. The APM tool (AppDynamics) and the Network Monitoring tool (ThousandEyes) are integrated bidirectionally through their API (out of the box, no custom integration is required).

The visibility provided by one tool is greatly enhanced by data coming from the other tool, that are correlated automatically and shown in the same console.

So, if you're investigating about a business transaction, you don't see just the performance of the software stack and its distributed topology, but also the latency, packet loss, jitter and more network metrics in the same context (exactly in the network segments that impact the traffic for that single business transaction, at that instant in time).

Similarly, if you're looking at a network, you immediately know what applications and business transaction would be affected if it fails or slows down. And automated tests can be generated to monitor the networks and the end points, that are created automatically from the topology of the application that the APM tool has discovered.

Exciting times are coming, the Operations teams can expect their life to be much easier when they start adopting a Full stack Observability approach. More detail in next posts...