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4 Strategies to Slash Observability Costs

Dotan Horovits
Logz.io

In a world where software systems rule the digital landscape, there's a lurking terror that goes bump in the code. It's called "observability," and you may not be prepared to pay its price.

Observability is essential for maintaining the performance and reliability of digital creations. Like a boat in shark-infested waters, it's a lifeline of modern software. But beware, for the cost of attaining the power of observability can quickly spiral out of control, like a monster lurking in the depths, waiting to strike when you least expect it.


In the darkest corners of the tech world, we hear the chilling cries of organizations, tormented by the relentless rise of the cost of observability. Every dollar spent on technology is scrutinized and dissected. Meanwhile, nefarious vendors take advantage of the desperate need for observability, charging terrifying fees to transport data to their unholy platforms, data that holds virtually no value.

But fear not, for there is a different path, a path to cost-effective observability. Join me as we venture into this cryptic world with practical tips to help you vanquish observability costs, without compromising your monitoring and troubleshooting prowess.

Tip #1: Optimize Your Data

In this haunted realm, one of the most pervasive villains is excessive and irrelevant data. Many organizations unwittingly ship massive volumes of metrics and logs, most of which are mere phantoms, holding no value. To banish this data demon, you must identify and capture only the meaningful data that affects your business. By filtering out the unnecessary, you can significantly reduce the cost of storage and processing, focusing your energies on what truly matters.

Thanks to the "mysteries" of machine learning, we can now unlock the secrets of multi-layer data optimization and distinguish between living and undead data. With the right tools, we can now visualize the metrics and logs that are truly alive, and ignore those that wander the land of the dead. Armed with this knowledge, you can make informed decisions, leading to substantial cost savings.

Tip #2: Manage Data Retention

Not all data deserves to ascend to the observability plane. Some data must be preserved, while others can be released into the ether. By managing data retention wisely, you can reduce storage costs without sacrificing your ability to troubleshoot and comply with the dark arts of regulations.

The key is to segregate your data based on specific use cases and retention requirements. Each use case should have its own set of retention policies, ensuring that the critical data lingers for the required duration while less important data meets its demise sooner. In this way, you can flexibly optimize costs, aligning data retention with its value and importance to your organization.

Tip #3: The Alchemy of Logs to Metrics

Sending logs is like sending a message to the beyond, but the true value lies in the insights that rise from the darkness. Many organizations find themselves drowning in the deluge of logs, trapped in a nightmarish maelstrom of data overload. However, by converting logs into meaningful metrics, you can refine data analysis, visualization, and alerting, all while reducing costs. No longer will you be haunted by the specter of high storage costs, for you can define parameters to generate metrics that unveil system performance, success rates, failure rates, and more.

Tip #4: Leverage Sub-Accounts for Cost Control

In the sprawling mansion of observability, managing costs can be as daunting as a haunted maze. One of the best ways to conquer the labyrinth is to provide cost accountability and autonomy to different teams within your organization.

By allocating specific budgets to sub-accounts, you can impose cost limits on each team while allowing them to manage their observability needs. This approach ensures teams are responsible for their spending and, if done correctly, casts a protective spell to ensure teams only see the data they need for their tasks, reducing compliance risks. Sub-accounts bring balance between autonomy and cost control, like a ghostly guide through the labyrinth of resource utilization and budget management.

End the Nightmare: Cost-Efficient Observability Can Be Your Reality

Observability, though essential, need not be a horror story of costs spiraling out of control. By heeding these practical tips, you can wrestle control from the observability cost beast, all while maintaining your monitoring and troubleshooting prowess.

Focus on meaningful data by utilizing data optimization techniques; convert logs into metrics; master the dark arts of storage and data retention policies; and wield sub-accounts for cost control — These are the keys to achieving cost-efficient observability, without compromising your critical monitoring processes.

So be brave enough to face the shadows and seek the observability you desire at a price that won't cost you an arm and a leg. When you do, the horror of observability costs shall haunt you no more!

Dotan Horovits is Principal Developer Advocate at Logz.io

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4 Strategies to Slash Observability Costs

Dotan Horovits
Logz.io

In a world where software systems rule the digital landscape, there's a lurking terror that goes bump in the code. It's called "observability," and you may not be prepared to pay its price.

Observability is essential for maintaining the performance and reliability of digital creations. Like a boat in shark-infested waters, it's a lifeline of modern software. But beware, for the cost of attaining the power of observability can quickly spiral out of control, like a monster lurking in the depths, waiting to strike when you least expect it.


In the darkest corners of the tech world, we hear the chilling cries of organizations, tormented by the relentless rise of the cost of observability. Every dollar spent on technology is scrutinized and dissected. Meanwhile, nefarious vendors take advantage of the desperate need for observability, charging terrifying fees to transport data to their unholy platforms, data that holds virtually no value.

But fear not, for there is a different path, a path to cost-effective observability. Join me as we venture into this cryptic world with practical tips to help you vanquish observability costs, without compromising your monitoring and troubleshooting prowess.

Tip #1: Optimize Your Data

In this haunted realm, one of the most pervasive villains is excessive and irrelevant data. Many organizations unwittingly ship massive volumes of metrics and logs, most of which are mere phantoms, holding no value. To banish this data demon, you must identify and capture only the meaningful data that affects your business. By filtering out the unnecessary, you can significantly reduce the cost of storage and processing, focusing your energies on what truly matters.

Thanks to the "mysteries" of machine learning, we can now unlock the secrets of multi-layer data optimization and distinguish between living and undead data. With the right tools, we can now visualize the metrics and logs that are truly alive, and ignore those that wander the land of the dead. Armed with this knowledge, you can make informed decisions, leading to substantial cost savings.

Tip #2: Manage Data Retention

Not all data deserves to ascend to the observability plane. Some data must be preserved, while others can be released into the ether. By managing data retention wisely, you can reduce storage costs without sacrificing your ability to troubleshoot and comply with the dark arts of regulations.

The key is to segregate your data based on specific use cases and retention requirements. Each use case should have its own set of retention policies, ensuring that the critical data lingers for the required duration while less important data meets its demise sooner. In this way, you can flexibly optimize costs, aligning data retention with its value and importance to your organization.

Tip #3: The Alchemy of Logs to Metrics

Sending logs is like sending a message to the beyond, but the true value lies in the insights that rise from the darkness. Many organizations find themselves drowning in the deluge of logs, trapped in a nightmarish maelstrom of data overload. However, by converting logs into meaningful metrics, you can refine data analysis, visualization, and alerting, all while reducing costs. No longer will you be haunted by the specter of high storage costs, for you can define parameters to generate metrics that unveil system performance, success rates, failure rates, and more.

Tip #4: Leverage Sub-Accounts for Cost Control

In the sprawling mansion of observability, managing costs can be as daunting as a haunted maze. One of the best ways to conquer the labyrinth is to provide cost accountability and autonomy to different teams within your organization.

By allocating specific budgets to sub-accounts, you can impose cost limits on each team while allowing them to manage their observability needs. This approach ensures teams are responsible for their spending and, if done correctly, casts a protective spell to ensure teams only see the data they need for their tasks, reducing compliance risks. Sub-accounts bring balance between autonomy and cost control, like a ghostly guide through the labyrinth of resource utilization and budget management.

End the Nightmare: Cost-Efficient Observability Can Be Your Reality

Observability, though essential, need not be a horror story of costs spiraling out of control. By heeding these practical tips, you can wrestle control from the observability cost beast, all while maintaining your monitoring and troubleshooting prowess.

Focus on meaningful data by utilizing data optimization techniques; convert logs into metrics; master the dark arts of storage and data retention policies; and wield sub-accounts for cost control — These are the keys to achieving cost-efficient observability, without compromising your critical monitoring processes.

So be brave enough to face the shadows and seek the observability you desire at a price that won't cost you an arm and a leg. When you do, the horror of observability costs shall haunt you no more!

Dotan Horovits is Principal Developer Advocate at Logz.io

Hot Topics

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...