With the fast-changing business environment turbocharged with the aftermath of Covid-19, companies are facing a paradox when it comes to modern infrastructure monitoring. While IT infrastructure has never been as simple to deploy and manage as it is today, it is seldom found in one place – large networks of assets in multiple locations have become the norm.
As a result, IT and engineering teams across the world are grappling with a growing network of complex systems, and the more mission-critical infrastructure monitoring is, the more complicated managing and monitoring becomes.
By taking steps to create visibility across their entire tech stacks, companies can create a modern environment and a culture of visibility while gaining full observability across their infrastructure.
Here are some steps that can be taken to solve complex infrastructure puzzles, define a framework to proactively detect anomalies, and automate the remediation procedures.
Shift the paradigm in your monitoring infrastructure
Traditional monitoring tools tend to be reactive and often run on-premise, which means that extra resources are required for proper configurations and ongoing management. By modernizing cloud-based infrastructure, organizations can maintain a competitive advantage by scaling quickly as required.
To fully observe modern environments, IT teams need to be able to assess their health in realtime and check the status of specific data points.
Modern environments need resilient systems that avert outages before they occur and decrease the overall downtime experienced. Being proactive in preventing outages vs reacting for alert floods and cascading incidents also allows for investment in future-proofing systems and moving towards greater automation.
Implement outcome-based dashboards that correlate data to provide insights and
Every organization is unique, and they have their own specific needs when it comes to setups.
Modern monitoring solutions may give some out-of-the-box insights, but their real power is in customization and applying AI/ML to deliver truly impactful outcomes. Finding and fixing problems is simplified when telemetry data is correlated across the stacks and tailored to the specific use cases that are important to a particular business.
Dashboards and visualizations need to be used as a gateway for outage prevention and as such should be adjusted to suit the needs of an individual business reporting tool that provides correlation and a visual display of organizational KPIs, metrics, and data. Executive dashboards should be put in place to give the C-suite at-a-glance visibility into customer experience, revenues protected due to downtimes averted, and infrastructure performance.
End the silos
By taking steps towards a modern, highly scalable, and available architecture, end-to-end visibility across the entire stack is made possible with seamless ease.
Modern monitoring solutions still typically require teams to switch between using different tools that operate across other parts of the stack. This wastes time and creates data silos that can lead to human error.
Furthermore, the use of different tools by different sections of the organization often leads to the creation of silos that present different values for different people but seldom provide a single unified view for efficient decision making and shorter analysis paralysis.
Seeing a system through an integrated, single pane of glass allows for a clear line of sight across an entire system and removes blind spots.
Achieve greater efficiency and scale
Being able to scale monitoring tools at the same pace as scaling infrastructure is vital. The combination of a modern infrastructure monitoring solution, in addition to AI/ML-driven tools, is key to enabling greater efficiency.
Proactively detecting anomalies and automating connections between incidents and events is vital to reducing noise and pinpointing critical infrastructure issues. Metadata and enrichment allow incidents to be diagnosed much faster, and the root cause can be found more quickly.
Creating visibility across the entire tech stack is about empowering teams to work smarter, not harder while ensuring that business objectives are met. While such objectives vary for each organization, the increasing complexity of the stack makes it important to understand relationships and connections between different entities.
Cloud computing in the post-2020 world has become the de facto choice of IT due to digital transformation shifts accelerated by remote work. Based on the growth seen in the industry, money is flowing toward Microsoft Azure and its software-as-service offerings as well as Amazon Web Services. Google Cloud Platform is also garnering interest for big data and analytics workloads.
Modern cloud platforms and infrastructure insights
While AWS held the leadership for so many years, over the last few years Azure has been cutting into this lead through its scalable and flexible platform that allows for deploying, building, and managing applications no matter where the organizations may be.
Microsoft Application Insights is an available IT tool that presents data around specific application anomalies and enables developers to track and monitor their website performance on Azure. It also helps detect loopholes that are dragging the application from reaching its potential performance with the help of powerful analytics, which helps diagnose issues and understand how users are trying to use one’s application. The main motive behind it is to give all the developers an optimum performance of their work and a best-in-class user experience.
While AppInsights provides the avenue for simplified infrastructure data viewing, it also requires teams to work around some of the challenges it presents. Prominent amongst those are:
- Inability to automatically identify a single root cause in enterprise systems with millions of dependencies
- Real-time discovery and visualization of enterprise-wide application topologies
- Auto-instrumentation and proactive remediation of infrastructure anomalies
- Ease of scalability and integration with enterprise technologies and packaged apps
To overcome these challenges, industry-leading solutions like HEAL can be used in conjunction with Azure Application Insights. HEAL correlates data across all layers within the infrastructure to deliver real-time insights into Microsoft Azure and everything running on it.
HEAL in conjunction with AppInsights can do the following:
- Ease installation to instrument thousands of hosts in a matter of hours
- Full-stack auto-discovery
- Code performance monitoring
- Real user monitoring
- Auto-determine root cause
- Proactive detection and remediation
HEAL’s preventive healing solution adopts patented AI/ML techniques that map an application’s workload to its underlying behavior and learn these workload-behavior correlations over a period so they can flag anomalous transaction patterns or behavioral metrics ahead of incidents. This helps in true predictive detection of issues before they even occur and allows for remedial steps to be put in place so the outages can be averted. Some modes of preventive healing include dynamically optimizing or shaping the workload so the underlying system behavior remains unaffected, dynamically provisioning additional resources in cloud environments so that the system can handle workload surges, or projecting resource requirements based on a what-if analysis of future workload trends so that businesses can perform app-aware scaling.
HEAL delivers 3 different use cases:
Proactive infrastructure monitoring is vital to modern environments and can help businesses reduce operational costs and improve productivity. When combined with technologies like AI and ML, businesses can gain ‘at-a-glance visibility’ into customer experience, cost savings, and infrastructure performance to deliver impactful outcomes. HEAL’s preventive healing solution leverages AI/ML techniques to detect early warning signals, quickly solve the problem, and provide a lasting solution.