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Majority of Organizations Cannot Realize Full Potential of Observability

Although 78% of organizations surveyed have an observability practice in place, 91% said they face challenges that prevent them from realizing the full potential of the systems they have already deployed, according to Observability and Demystifying AIOps, a report from Chronosphere and the Enterprise Strategy Group (ESG).

Scalability and reliability of the observability tools were cited as the top concerns.

Additional survey findings include:

Observability tool sprawl is expanding

A majority of organizations reported at least 6 different tools in use, with more than half (52%) using 11-20 different tools. The report also shows that 72% of organizations agree that the number of tools they use adds complexity.

Explosive observability data growth

Additionally, 69% of survey respondents reported that the most costly line item for most observability solutions, data storage, is growing. Respondents stated that "the amount of observability data is growing at a concerning rate" and one in five respondents reported that this explosive data growth was their top concern.

To address data growth, organizations are taking a mix of steps to rein in costs, including:

■ increasing storage spend (52%)

■ limiting the number of observed applications in their environment (44%)

■ limiting the number of observed metrics per application (43%).

Cloud is greatest Observability challenge

Many respondents also noted that applications deployed in the cloud were harder for them to monitor and few of them felt that their observability solution was helping them meet their availability goals.

When asked about their biggest observability challenges, 60% agreed that "Lack of visibility into our cloud applications makes achieving SLAs a challenge," and only 20% chose "Improved SLA Performance" as one of their monitoring/observability strategy's most impactful benefits.

Methodology: TechTarget’s Enterprise Strategy Group (ESG) surveyed 374 IT (58%) and DevOps/AppDev (42%) professionals responsible for evaluating, purchasing, managing, and using observability at large midmarket (500 to 999 employees) (11%) and enterprise (1,000+ employees) (89%) organizations in North America (US and Canada).

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Majority of Organizations Cannot Realize Full Potential of Observability

Although 78% of organizations surveyed have an observability practice in place, 91% said they face challenges that prevent them from realizing the full potential of the systems they have already deployed, according to Observability and Demystifying AIOps, a report from Chronosphere and the Enterprise Strategy Group (ESG).

Scalability and reliability of the observability tools were cited as the top concerns.

Additional survey findings include:

Observability tool sprawl is expanding

A majority of organizations reported at least 6 different tools in use, with more than half (52%) using 11-20 different tools. The report also shows that 72% of organizations agree that the number of tools they use adds complexity.

Explosive observability data growth

Additionally, 69% of survey respondents reported that the most costly line item for most observability solutions, data storage, is growing. Respondents stated that "the amount of observability data is growing at a concerning rate" and one in five respondents reported that this explosive data growth was their top concern.

To address data growth, organizations are taking a mix of steps to rein in costs, including:

■ increasing storage spend (52%)

■ limiting the number of observed applications in their environment (44%)

■ limiting the number of observed metrics per application (43%).

Cloud is greatest Observability challenge

Many respondents also noted that applications deployed in the cloud were harder for them to monitor and few of them felt that their observability solution was helping them meet their availability goals.

When asked about their biggest observability challenges, 60% agreed that "Lack of visibility into our cloud applications makes achieving SLAs a challenge," and only 20% chose "Improved SLA Performance" as one of their monitoring/observability strategy's most impactful benefits.

Methodology: TechTarget’s Enterprise Strategy Group (ESG) surveyed 374 IT (58%) and DevOps/AppDev (42%) professionals responsible for evaluating, purchasing, managing, and using observability at large midmarket (500 to 999 employees) (11%) and enterprise (1,000+ employees) (89%) organizations in North America (US and Canada).

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Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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Broadcom

From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...

Today, organizations are generating and processing more data than ever before. From training AI models to running complex analytics, massive datasets have become the backbone of innovation. However, as businesses embrace the cloud for its scalability and flexibility, a new challenge arises: managing the soaring costs of storing and processing this data ...