Introduction

The expenses associated with collecting, storing, indexing, and analyzing data have become a considerable challenge for organizations. This data is growing as fast as 35% a year, multiplying the problems. This surge in data comes with a corresponding rise in infrastructure costs. These costs often force organizations to make decisions about what data they can afford to analyze, which tools they must use, and how and where to store data for long-term retention. These are often difficult choices and force the hands of the teams trying to manage and analyze this data. This can result in heavy, random sampling or eliminating data sources altogether which can severely impact the visibility into the security and stability of underlying IT systems. An observability pipeline can help solve these challenges.

What is an Observability Pipeline?

An Observability Pipeline or Telemetry Pipeline is a sophisticated system designed to manage, optimize, and analyze telemetry data (like logs, metrics, and traces) from various sources. It helps Security and DevOps teams efficiently parse, route, and enrich data, enabling them to make informed decisions, improve system performance, and maintain security within budgetary constraints. Observo.ai elevates this concept with AI-driven enhancements that significantly reduce costs, enhance security posture, limit risk, and improve operational efficiency. In this article, we will explore some of the top advantages of using an AI-powered observability pipeline.

Reduce Costs by over 50%

SIEMs and log analytics platforms are valuable tools for identifying potential security threats, enhancing visibility into security events, mitigating potential risks, and investigating security incidents. While pricing varies by vendor, license costs are typically driven by the maximum daily data volume ingested and indexed. For large companies, this can be millions or tens of millions of dollars annually. In addition to SIEM and logging license costs, companies can spend as much or more on infrastructure - primarily storage and compute costs. Because most companies retain data for 6 months or more, all of that ingested data racks up huge storage costs, and the bloated analytics index requires more computing power to quickly retrieve query requests.

AI-powered pipelines like Observo.ai can help cut these costs by dramatically reducing the volume of data ingested into analytics platforms without losing any of the signals of ingesting full-fidelity data. Observo.ai can typically reduce volume by as much as 70% after a couple of hours of configuration. Because the AI/ML models of Observo.ai are constantly learning about the changing nature of this data, over time, many customers optimize and reduce their data by more than 80%. This is achieved by reducing noisy data elements and summarizing “normal” events so that SIEMs and logging tools can focus on analyzing only more interesting data. By removing noisy or uninteresting data, your analytics platforms can focus on 20% of the data that contains all of the interesting events and signals that need further investigation. 

This data optimization and reduction has an immediate cost savings impact on reducing infrastructure costs. Reducing ingested data means storing far less data within your SIEM index. This can have a significant impact on storage costs. A leaner index also requires less compute resources which can help eliminate extra spending on servers in on-premises environments or for cloud expenditures.

Because of data retention requirements, companies are still required to keep raw, full-fidelity data for 6 months or longer depending on legal and industry-specific requirements. Observo.ai helps create a searchable, full-fidelity security data lake in low-cost cloud storage like AWS S3 or Azure Blob. Data is stored in Parquet file format making it highly compressed and searchable. Customers can use natural language queries, so they don’t need to be a data scientist to retrieve insights. Data stored in this way costs only 1% of the cost to store it in block storage within your SIEM or log analytics index. More aggressive customers can drop data from their index after a week or two and use Observo.ai to retrieve data on-demand, rehydrate it, and stream it back to their analytics tool should they need further investigation. Since the vast majority of queries are performed on data from the last 48 hours, this can create massive cost savings without interrupting security operations.

Observo.ai helps reduce data volume to reduce the costs of SIEM and logging tool infrastructure which can reduce total observability and security costs by as much as 50% or more. Read how Observo.ai helped a Global 1000 company cut total Splunk costs by 50%.

Maximize Security, Minimize Risk

Blindspots in security can happen when the organization overlooks critical information about its IT environment. Multiple factors including data verbosity often drive decisions about what data to analyze to secure the enterprise, ingest limits, compliance requirements, and the complexity of integrating into the SIEM. These decisions often place budget and other resource constraints above the strongest security posture possible. As a result, valuable data sources like VPC Flow Logs or Application Logs are deemed too expensive or too complicated to include in their analytics operations. By the same token, trying to analyze data with little analytical value and riddled with noise can overwhelm the security team’s ability to focus on actionable data.  

Observo.ai uses AI/ML to transform various data sources for easy and insightful integration with SIEM platforms. By separating interesting, high-signal data from less interesting data, Observo.ai helps security teams analyze more of the right data to get a complete picture of their security standing. By reducing the volume of less interesting data, they can do this without impacting their license budget, and as mentioned earlier, reducing their infrastructure spending. 

Ensuring compliance with standards for data privacy and data retention is an increasingly important priority for organizations. The fear of fines but more importantly, of losing customer trust is driving this shift in priorities. Data retention standards are changing, some industries mandate full data storage for as much as 7 years. Observo.ai makes it easy to create a data lake to normalize and securely store data for longer periods with significant cost savings. Observo.ai can also detect sensitive data, allowing you to secure it through obfuscation or hashing. Unlike static tools that set rules for what is sensitive data, Observo.ai uses pattern recognition to discover all sensitive data, even if it’s in an unexpected field or metric. Observo.ai helps you automate compliance with privacy regulations like GDPR, CCPA, and PCI. Read how a large data management and AI software company used Observo.ai to automatically detect and mask sensitive data to better comply with GDPR and other regulations.

Using an AI-powered data pipeline like Observo.ai helps organizations analyze more sources for a more complete picture without increasing budget, protect sensitive data, resolve incidents before they spiral out of control, and stay in compliance.

Optimize & Route Telemetry Data Flexibly

Vendor lock-in is a real challenge for organizations who prefer choice for how they analyze security and DevOps data. Observability pipelines powered by AI can route data from any source to the place or places where it has the most value. Observo.ai allows DevOps and security teams to choose the right mix of tools for their needs regardless of schema. It optimizes what types of data need to be analyzed by the most expensive tools and which can be routed to a more cost-effective tool. For instance, ingest Cisco Firewall events and Windows event logs from Kafka. It sends the optimized data to Azure Sentinel and full-fidelity data to a Snowflake data lake. These teams won’t need to collect data in multiple formats for every tool. With Observo.ai, data is collected once and routed where it has the most value. Observo.ai models automate this so an expert isn’t needed to establish a long list of rules tailored to each data type. Pipelines are drag-and-drop and can optimize data in just a few hours.

Observo.ai pipelines can also enrich data within the stream to provide more context. Observo.ai adds third-party data like Geo-IP and threat intel for better routing and deeper context. Enriching data can speed up queries and reduce the CPU toil of your SIEM and analytics platforms. Read how a major hospital system used Observo.ai to enrich log data with more context and routed more data types to Azure Sentinel.

Speed Incident Resolution by over 40%

Security and DevOps teams are busy ensuring the security, stability, performance, and overall general health of their IT infrastructure. Unfortunately, a wide array of challenges stifle those efforts. Growing volumes of security and observability data filled with noise makes it very difficult to find actionable insights even with advanced analytics tools. Daily data limits force these teams to spend cycles of their time manually trying to fit more data into smaller spaces.  The AI-powered observability pipeline from Observo.ai can supercharge team productivity. Observo.ai automates data optimization so teams can focus on more important tasks including resolving critical incidents. 

Observo.ai also cuts through the noise of alert fatigue by enriching your data with AI-based sentiment analysis so your teams prioritize the most important alerts. The Observo.ai pipeline learns what is normal for any given data type. The Observo.ai Sentiment Engine identifies anomalies and helps teams prioritize which alerts can be set aside for later analysis and which must be dealt with right away. Our customers have reported a speeding up of incident resolution by as much as 40%. Read how a SaaS company boosted developer productivity, shortened issue debugging times by 42%, and cut more than 20% off their software delivery cycles.

Conclusion and next steps

The challenges posed by escalating data volumes and related infrastructure costs call for innovative solutions for organizations striving to maintain efficient operations and robust security postures. AI-powered observability pipelines, like Observo.ai, streamline data management, optimize resource utilization, and enhance security and observability analytics capabilities. By reducing data volume, minimizing noise, and automating incident resolution processes, Observo.ai empowers organizations to maximize the value of their data while minimizing costs and mitigating risks. With its ability to facilitate compliance efforts, streamline data routing, and prioritize actionable insights, Observo.ai is a pivotal tool for organizations looking to solve their most pressing telemetry data challenges, empowering security and DevOps teams with automated pipelines that continue to learn and improve.

• For more on Observo.ai, read our white paper “Elevating Observability: Intelligent AI-Powered Pipelines.”
• Watch our explainer video for a high-level tour of Observo.ai.
• For a deeper dive into our solutions, request a demo.