In a world where security budgets are scrutinized and shelfware is an ever-present risk, it's surprising to see one of the oldest cybersecurity categories—SIEM (Security Information and Event Management)—forecasting growth numbers that would make a startup jealous. According to IDC’s Worldwide Security Information and Event Management Forecast, 2025–2029: Continued Payment for One’s SIEMs*, the global SIEM market is expected to grow at a double-digit clip through 2029, powered by cloud adoption, regulatory momentum, and an evolving set of customer needs.
But this isn’t your legacy SIEM story. The category is undergoing a metamorphosis.
Cloud is Carrying the Market
One of the biggest drivers behind SIEM's renewed growth is the accelerating shift to the cloud. Cloud-based SIEM platforms are now the norm rather than the exception, and their adoption is surging across organizations of all sizes. In fact, cloud deployments are expected to account for more than three-quarters of SIEM revenue in just a few years.
Why the rush? For one, cloud SIEMs offer a faster time to value. Security teams can spin up environments without the hassle of provisioning hardware or navigating complex on-prem installations. Scaling up or down is easier too—organizations can adjust to meet growing telemetry volumes or evolving threat landscapes without a forklift upgrade.
Cloud SIEMs also align better with today’s distributed infrastructure. As workloads move to hybrid and multi-cloud environments, centralized cloud-native SIEMs make more sense architecturally. They provide unified visibility, continuous updates, and increasingly advanced analytics capabilities, including embedded machine learning and GenAI.
But the cloud isn’t a silver bullet.
There are real complexities that come with moving SIEM to the cloud:
Cost Predictability: While the cloud makes things easier to deploy, it doesn’t always make them cheaper. Many cloud SIEMs use data ingestion-based pricing, which can lead to spiraling costs as telemetry grows. Without careful pipeline management, teams may be paying to ingest a lot of low-value or redundant data.
Latency and Performance: Query performance can be inconsistent, especially when pulling from massive, multi-region datasets. For teams that need real-time alerts and fast investigations, lag can be a real operational risk.
Data Residency and Compliance: For global organizations, cloud SIEMs introduce tricky questions about where data lives and whether it can legally cross borders. Vendors need to offer flexible storage options and comply with increasingly strict data sovereignty rules.
Vendor Lock-In: Many cloud-native SIEMs are deeply integrated with a specific cloud provider’s ecosystem. While that tight integration has benefits, it can also limit flexibility and make future migrations painful.
Security of the Security Tool: Ironically, moving SIEMs to the cloud introduces new layers of attack surface. Misconfigurations in access controls or integration pipelines can create vulnerabilities within the very system designed to monitor and detect threats.
In other words, while cloud-based SIEMs are clearly the future, they require thoughtful planning and strong operational discipline. Success depends not just on choosing the right platform, but on aligning pricing models, access strategies, and data architecture to the needs of a modern security team.
Costs Are Climbing—And Customers Are Feeling It
Even with the market growing and cloud adoption booming, there’s an elephant in the room: SIEMs are expensive. And in many cases, they’re getting more expensive over time.
One of the primary culprits is the dominant pricing model—charging based on the volume of data ingested. As organizations collect more telemetry from endpoints, networks, cloud infrastructure, identity platforms, SaaS apps, and more, their SIEM costs grow in parallel. This creates a perverse incentive: the more visibility you try to achieve, the more it costs you to maintain that visibility.
That’s a tough pill to swallow for security teams who are told they need to "log everything" to stay protected. And it’s even harder for those in industries with strict compliance requirements that mandate long-term data retention.
To make matters worse, much of the data being ingested isn't actionable. Logs may be verbose, redundant, or lacking the key attributes needed for effective detection and response. As a result, teams often pay a premium to ingest data they can’t even use.
This is where telemetry pipelines come in—and they’re quickly becoming one of the smartest investments a security team can make.
Why Telemetry Pipelines Matter
A telemetry pipeline is an intermediary layer that processes data before it reaches the SIEM. Think of it as a smart filter and optimizer for your logs and events. Done right, it can dramatically improve both the cost-efficiency and effectiveness of your SIEM deployment.
Here’s how:
Noise Reduction: Pipelines can strip out repetitive or low-value log entries—like heartbeat messages or debug-level logs—before they’re ingested. This alone can reduce SIEM costs significantly without sacrificing meaningful visibility.
Field-Level Filtering: Instead of sending entire log payloads, pipelines can extract only the fields needed for security use cases (e.g., usernames, IP addresses, timestamps). That makes the data leaner, faster to search, and cheaper to store.
Data Enrichment: Pipelines can enrich events with contextual metadata (such as asset tags or geo info) before they hit the SIEM. This increases their utility for detection and investigation—meaning you get more value from each event you’re paying to store.
Routing by Relevance: Not all data needs to go to the SIEM. Telemetry pipelines can route less critical logs to cheaper storage solutions—like data lakes or blob storage—while sending high-priority events to the SIEM in real time. This hybrid model allows for deeper investigation when needed, without blowing up your SIEM bill.
Normalization and Standardization: Pipelines help normalize data from diverse sources into a consistent format, which makes it easier to write detections, correlate events, and automate workflows.
Taken together, these advantages make telemetry pipelines one of the most powerful tools available to teams looking to optimize their SIEM strategy. They turn the cost equation from “log less or pay more” into “log smart and pay strategically.”
A Smarter Approach to Storage: Tiered Data, Unified Visibility
Today’s security teams are drowning in telemetry. Logs are generated from everywhere—cloud workloads, endpoints, SaaS platforms, APIs, identity systems, and beyond. But not all data is created equal, and treating it that way—by sending everything into the SIEM—can be both technically inefficient and financially unsustainable.
What security teams really need is a more flexible storage strategy: one that allows them to tier their data based on value, cost, and urgency, while still preserving the ability to search across everything in one place.
This is where the concept of tiered data architecture meets the "single pane of glass" vision.
High-value, high-frequency telemetry—like authentication logs, threat alerts, and privilege escalations—belongs in hot storage, directly accessible to the SIEM for real-time correlation and detection. But lower-value or long-tail data, like verbose application logs or compliance records, can live in cold storage or a data lake. These records are still important for investigations, audits, or threat hunting—they just don’t need to drive real-time decisions.
The key is ensuring all this data remains queryable, even if it’s not all in the SIEM.
That’s where security data lakes come in. They provide a cost-effective, scalable way to store large volumes of raw telemetry in its original form. When paired with flexible analytics tools, they allow security teams to query this data on-demand—without duplicating it or ballooning their SIEM costs.
When this model is done right, it delivers:
Cost savings by keeping expensive SIEM ingestion tightly focused
Retention flexibility for meeting regulatory and business requirements
Enhanced investigations with the ability to go deep into historical data
Operational simplicity with unified access and visibility across data tiers
This hybrid model—tiered storage with unified visibility—is becoming the new standard for modern security architecture. It strikes a balance between performance, cost-efficiency, and investigation depth. And most importantly, it allows security teams to ask better questions of more data, without being held hostage by traditional pricing and architecture limitations.
In a threat landscape that’s constantly evolving, being able to see everything, but store it smartly, might be the most strategic decision a security team can make.
The Bottom Line
SIEM is no longer just a compliance checkbox or a legacy system collecting dust in the corner of the SOC. It’s evolving—fast. Fueled by cloud adoption, increased regulatory scrutiny, and the explosion of telemetry data, SIEM is seeing a level of growth and innovation that few expected from such an established category.
But with that growth comes new pressure.
Security teams are grappling with rising costs, operational complexity, and the challenge of extracting value from an overwhelming volume of data. The traditional “ingest everything into the SIEM” model is giving way to a more thoughtful approach—one that blends real-time visibility with smarter data management.
Modern architectures are prioritizing flexibility: telemetry pipelines to filter and enrich data before it hits the SIEM, security data lakes to handle scale and retention, and tiered storage strategies that align cost with value. Crucially, teams want all this infrastructure to work together seamlessly—to see and query everything, regardless of where it lives.
In this new era, the winners won’t just be those who log the most. It’ll be those who build agile, efficient systems that give security teams fast, unified access to the right data—at the right time, at the right cost.
SIEM isn’t going away. But how we use it—and how we architect around it—is being redefined.