Event Correlation and Automation
AIOps to reduce IT noise and prevent crippling outages
The typical enterprise has invested in 15 or more observability and monitoring tools. These tools were designed to provide IT Ops, NOC, DevOps and SRE teams visibility into critical applications, systems and infrastructure, both on-prem and in the cloud.
Unfortunately, over time, the aggregation of these tools has led IT teams to a dizzying number of alerts, lack of valuable insights and an increase in manual reporting. As a result, outages, incidents & performance problems persist.
BigPanda is a best-in-class event correlation platform powered by AIOps. Identified by GigaOm as among the strongest AIOps players, the platform helps modern enterprises reduce IT noise by 95%+, lets you detect incidents in real-time, as they form and before they escalate into outages, and empowers your IT Ops team to focus on high-value work.
Event Correlation for modern IT environments
BigPanda was purpose built for Event Correlation and Automation, aggregating and connecting alerts, changes and topology data to detect incidents as they occur, in real-time, preventing them from escalating into outages.
Using 50+ out-of-the-box integrations and powerful REST APIs, BigPanda connects to existing observability and monitoring tools and aggregates their data in real-time. To date, BigPanda has integrated with 300+ unique tools.
Additionally, BigPanda’s SNMP agent collects alerts (SNMP traps) from tens of thousands of IT systems and devices. The system normalizes the data into a consistent format and adds context by bringing in topology and operational data.
Using Open Box Machine Learning, BigPanda converts the inputs into a handful of context-rich incidents, dramatically reducing noise. Rather than adding more monitoring, BigPanda gives you more intelligence from your existing tools.
BigPanda solves multiple challenges for IT managers
Disparate data, manual aggregation
For enterprises, critical operational data is distributed across dozens of siloed tools. Without a solution in place that can aggregate this data, teams are forced to constantly switch between those tools, and make sense of it manually.
Inability to make sense of the data without experts
Different tools use distinct formats and terminology to describe the same IT components. This makes it difficult for operators to consume their data in a consistent manner, and almost impossible to glean valuable insight.
Lack of cross-stack visibility and context
Monitoring tools are siloed from each other, making it difficult to connect the meta-data from one data stream with the meta-data from other data streams. This inability to connect the dots leads to limited visibility into the scope of incidents and outages, and their root cause. The result: costly and frustrating human interactions as different operators and team members try to determine what has been impacted and what to focus on next.
With 15+ siloed monitoring tools generating tens or hundreds of thousands of alerts each day, critical incidents are often too hard to spot in the sea of data exhaust. Teams are made aware of an outage when frustrated customers, users, service owners and business units start to complain.
Manual reporting and analysis of IT operational performance
Many enterprises rely on error-prone, manually updated spreadsheets or general purpose reporting tools that require extensive customization to report on IT Ops data. Other organizations rely on homegrown/custom IT Ops reporting tools that are expensive and time-consuming to build and maintain. These manual, homegrown reporting systems make it expensive and nearly impossible for enterprises to track, measure and improve critical IT Ops KPIs and metrics in a timely manner.
Using 50+ out-of-the-box integrations and powerful REST APIs for monitoring alerts, changes and topology, BigPanda can collect and aggregate data from all monitoring, change and topology tools in real-time.
How BigPanda’s IT Ops Event Correlation works
Normalizing data into a single and consistent format
BigPanda translates diverse IT data sets into one consistent taxonomy, using general purpose key-value pairs called tags. BigPanda performs this in real time using multiple out-of-the-box and custom normalization methods.
Enriching monitoring alerts with operational and topology data
BigPanda’s out-of-the-box integrations and REST API let teams collect contextual data from all sources of operational and topology data including CMDBs, asset and topology sources, infrastructure-as-code sources, APM / network maps, custom asset and process inventories. This data, once collected, is used to enrich monitoring alerts. BigPanda’s native capabilities offer the ability to enrich millions of records in real time. This is especially important for enterprises whose application topology data is scattered across several sources.
Reducing noise without manual effort
BigPanda uses Open Box Machine Learning to correlate alerts, changes and topology data to reduce IT noise by more than 95%. BigPanda does more than just reduce noise. By eliminating informational events or false positives, IT operations teams can now detect evolving incidents as they happen before they escalate into crippling outages.
BigPanda tailors its Machine Learning for each enterprise’s unique needs. In order to maximize correlation efficiency, BigPanda also provides users with unprecedented control over its Machine Learning logic. BigPanda allows users to see the logic in plain English and incorporate their tribal knowledge. Users can test and preview results, all before deploying this logic into production. Open Box Machine Learning also allows enterprises to pragmatically adopt AI/ML to benefit from automation.
Easy impact analysis and prioritization
BigPanda’s Operations Console and Real-time Topology Mesh make it easy for operations teams to understand the impact of incidents and prioritize their response. The console provides cross-stack views, filtered by severity. The console also displays business context, such as affected services and potential customer impact for each incident, in the intuitive incident view. The console supports practices such as Inbox Zero to help operators prioritize their to-do lists for incidents. Finally, the Real-time Topology Mesh helps users understand dependencies between apps/services and low-level infrastructure, so they can determine how best to prioritize their responses to incidents.
Out-of-the-box reporting for IT Operations
BigPanda Unified Analytics is purpose built from the ground up for IT Ops. BigPanda’s domain-specific reporting and analytics experience is derived from years of helping the largest and most complex organizations in the world report on their IT Ops data. It also offers a fully customizable and scalable reporting and visualization back-end that can handle IT Ops data generated by some of the largest enterprises in the world.
BigPanda’s Unified Analytics provides enterprises with a library of out-of-the-box dashboards that can measure, track and display commonly used IT Ops Key Performance Indicators (KPIs), metrics and trends in accordance with industry best practices. These include KPIs and metrics such as Compression and Noise Reduction Ratios, Impacted Applications, MTTx by Severity and Category, Team Performance, Top N Hosts, Top N Applications, Enrichment Rates, Recurring Incidents and more. BigPanda Unified Analytics supports all widely used business intelligence and data warehousing platforms.
Watch this on-demand webinar and find out how to tell if you are running a chaotic or well-run incident management process.
Building the business case for IT Ops Event Correlation and Automation tools
To build a business case, quantify the negative consequences of having to manually sift through events to understand incidents. Here are some questions enterprises commonly use to quantify the status quo:
What is the value of each minute spent on your IT Ops alerts, incidents and outages when you don’t have Event Correlation and Automation in place?
- How many FTEs does your IT Ops or NOC teams have (across all the shifts, and across your global locations)?
- What are their salaries and fully loaded costs?
For the IT Ops alerts you collect:
- What % is just noise / non-actionable / merely informational?
- How long does it take your IT Ops team to examine each alert, understand what it means, acknowledge it and then archive/delete it?
- What are the cumulative man-hours your team spends doing this task? What is the associated cost?
How often are outages reported by teams outside of IT?
- Why did those get missed?
- What is the financial and reputational impact of these outages to the business?
What is the non-human cost of outages to critical business systems, such as:
- Revenue generating systems
- Point of sale (POS) systems
- Payment processing services
- SLAs that are violated
If you have a homegrown or custom Event Management or Event Correlation solution, consider quantifying these costs:
- Engineering time and costs required to build and maintain the solution
- Hardware costs to host the solution
- Admin time required to administer and maintain the solution
- Admin time required to customize the solution on an ongoing basis to keep it in sync with new tools and business requirements
- Engineering time required to add new features and functionality periodically
- Engineering time required to upgrade the solution to help it scale with growth
If you have an ineffective legacy/commercial Event Management solution, consider quantifying these costs as you build a business case for Event Correlation:
- Annual software licensing costs, if applicable
- Annual software support and maintenance costs
- The cost of having an army of FTE admins that must maintain the solution
- The cost of bringing in expensive 3rd party System Integrators or consultants to handle every new business requirement or tool integration
Just by looking at the questions above, you probably have a good idea of the potential ROI BigPanda can deliver to you and your team.
So, what are you waiting for?