From Datadog to Grafana Cloud: Why companies migrate and how it changes business for the better
“Impossibly expensive.”
“Generic database metrics.”
“Exceeding limits.”
“No transparency.”
These are the words our customers use to explain why they looked for a Datadog alternative and migrated onto Grafana Labs’ observability solutions.
Grafana Cloud provided the scalability that LexisNexis Risk Solutions needed to migrate acquired companies into a unified observability platform. “We’ve had migrations from Datadog. We’ve moved from Elastic,” Neil Wilson, Director of Software Engineering at LexisNexis, said at ObservablityCON 2024. “Grafana has been really the key to helping show us the way to do it.”
With the fully managed Grafana Cloud offering, “you get cost savings, great community-driven tools, and the flexibility to fine-tune things for your organization. It’s a solid platform,” said an engineer at a financial software company that recently migrated off of Datadog.
Many observability teams — from Fortune 100 companies to popular start-ups — would agree. Over the past two years, we’ve welcomed numerous companies that moved from Datadog to Grafana Cloud. This is all part of what we see as an ongoing trend of moving away from proprietary platforms in favor of an observability platform that is transparent, cost-effective, and based on open standards.
In this blog post, we highlight why users chose Grafana Cloud as an alternative to Datadog — and the benefits they’ve experienced since making the move.
1. Cost savings
Unpredictable bills and cost were some of the top concerns for practitioners, according to Grafana Labs’ 2024 Observability Survey.
The common refrain in the industry is that “we want to get the most value out of each dollar that we spend,” said Ramiro de Zavalia, Staff Site Reliability Engineer at ASAPP, an AI-driven software firm that migrated to Grafana Cloud.
Sometimes it’s hard to tell which platform will deliver on that promise. But in a recent price comparison by the cloud cost management company Vantage, the conclusion was that “Grafana Cloud and Datadog both offer full monitoring platforms, with Grafana’s main strength being in its customizability and Datadog’s in its unified approach and extensive integrations. However, Grafana Cloud is often significantly more affordable, especially in scenarios with many hosts, making it the cost-effective choice for many organizations.”
Grafana Cloud users credit that to two factors: transparency and tooling.
For one global payments provider, the struggle to control their observability costs around custom metrics and logs was not about lack of discipline on the part of engineers, but the lack of insight from the vendor.
With Datadog, “we were spending quite a lot,” said an engineer at the company, “and it was difficult to reduce costs because it was opaque to figure out what to cut.”
A cybersecurity company had a similar experience. While engineers had been veteran users of Datadog in their legacy stack, ultimately the experience didn’t add up to savings because they couldn’t control the influx of data as they scaled.
When that company migrated to Grafana Cloud, they found that even as novices to the platform, they got expert-level insight and assistance from the Grafana Labs team. “The team was able to troubleshoot issues, and ultimately helped us optimize our spend,” an engineer from the company said. “There was much more transparency and visibility into how the costs were calculated."
In fact, another customer, a provider of point-of-service payment services, saved roughly 40% after migrating off of Datadog.
Adaptive Metrics
Since 2023, we’ve gone a step further in giving that level of savings to all Grafana Cloud users directly. With Adaptive Metrics, a feature that helps cut costs by aggregating unused and partially used metrics into lower cardinality versions, Grafana Cloud users have been able to cut metric costs by an average of 35%.
Actian, the data analytics and management division of HCLSoftware, saw a “dramatic cost reduction” when they migrated from their three previous observability platforms to Grafana Cloud — and expect even further cost savings as they continue to ramp up with Adaptive Metrics.
More importantly, the savings have translated into an equal investment in observability across their organization.
“It’s the same code, the same agent, the same level of observability and dashboards, so we can see a problem earlier in the development environment and fix it before it goes to production,” said Actian Lead Cloud Operations Engineer Suleyman Kutlu. “We have the ability with Grafana to implement the same level of observability in every environment. In the past, this was not possible because of costs.”
Palantir, the Denver-based software company that specializes in big data analysis, transitioned from Datadog to Grafana Labs’ observability tools to consolidate its systems as the business reached hyper scale. “Grafana Labs’ solutions have allowed us to unify our observability tools across all environments, significantly reduce costs, and improve our operational efficiency,” noted Greg DeArment, Palantir’s Head of Production Infrastructure.
One senior platform engineer from another global payments platform summed up their migration even more simply: “The effort feels like an investment to have flexibility in how we collect telemetry and what we’re charged for.”
2. Open source, open standards, OpenTelemetry
OpenTelemetry’s popularity has grown exponentially with 2024 seeing a 2x rise in Google searches and GitHub PRs related to the open source project. In fact, 85% of respondents to our Observability Survey said they were using the open source observability framework for telemetry data in production or investigating it.
The ComplyAdvantage team includes longtime OpenTelemetry fans, favoring its vendor-neutrality and drop-in instrumentation. “You can start off with just a few lines of code and get maximum benefit from it,” said ComplyAdvantage Principal SRE Adam Wilson at ObservabilityCON 2023.
The same could not be said for ComplyAdvantage’s experience using Datadog. They quickly discovered their open source mindset didn’t play well with proprietary tools. “It was very much like we were talking different languages,” Wilson said.
Open source and open standards turn out to be the universal language that many companies want to hear.
To enable interoperability, support for the OpenTelemetry format has been natively built into tooling across the Grafana Cloud platform — from our metrics, logs, and traces backends to Application Observability and more — so that teams don’t need to re-implement SDKs or learn new telemetry formats if they move from one platform to another.
As a result, one American insurance company that migrated from Datadog to Grafana Cloud called the process “straight forward” because of OpenTelemetry instrumentation.
ComplyAdvantage echoes the sentiment. In their new Grafana Cloud infrastructure, their application monitoring data goes into their gateways, which now use span metrics. Every trace that flows through that first layer of OpenTelemetry gateways has its metadata and metrics extracted and then shipped straight to Grafana Cloud.
In other words, said Wilson, “it just made absolute sense.”
3. The single pane of glass
Kubernetes clusters scattered across three cloud providers. Teams building custom observability stacks. Telemetry signals stored in different tools for different signals all with different agents.
The struggle to unify data into the single pane of glass is real. But navigating disparate data sources is a specific issue that Grafana Cloud was built to solve. “We believe that data is everywhere and our customers have many vendors, many databases, many teams using different technologies,” Grafana Labs CEO and co-founder Raj Dutt said on “NYSE Floor Talk.” “Grafana will help you understand your systems no matter where you data lives without having to consolidate everything into a single database.”
As a result, companies that move off Datadog and consolidate their disparate data in Grafana Cloud point to this as a key benefit.
Actian runs a distributed IT infrastructure that consists of more than 70 Kubernetes clusters spread across AWS, Azure, and Google Cloud. To gain visibility into that infrastructure, the team used to rely on a mix of three different observability tools — and three different agents — for synthetic monitoring, metrics, and logs.
Seeking a solution to simplify their monitoring environment, they turned to Grafana Cloud. “We now have one tool for anything and everything [related to] observability,” said Actian’s Kutlu during a talk at ObservabilityCON 2023. “We don’t need to switch between consoles in order to analyze a crisis or an incident.”
A global payments platform found similar rewards. “Having one tool for everything has helped a lot with debugging and collaboration,” said a senior engineer.
That team was even able to evolve their alerting strategy by creating reusable alerts and dashboards in Grafana for all teams.
“In Datadog, each team had to set up their own, which caused mistakes or missing coverage,” said one senior platform engineer. “We can set up common alerts for every application, which teams can subscribe to, and it saves them from reinventing the wheel.”
For ComplyAdvantage, the ultimate proof of success for Grafana’s single pane of glass came with how observability directly affected its business. “The big thing for us was the change in the way that people started to tell stories with data,” Wilson explained. The company’s CEO, for example, now uses infrastructure data to help shape conversations with customers and partners about how they’re using ComplyAdvantage.
Said Wilson: “Being able to have that impact on product, on sales, on that side of the business — from getting some request headers into our applications — was revolutionary.”
4. Improved developer productivity and deeper insights
Sometimes you really don’t get what you pay for. When one finance software company needed deeper insights into their metrics and better support for their multi-cloud observability stack, they found that Datadog couldn’t deliver.
“Datadog gave us generic database metrics,” said a senior software engineer at the company, who credits Grafana Cloud’s Amazon CloudWatch solution for providing richer database monitoring capabilities. “We now have the engine-level insights we needed for Postgres, which Datadog couldn’t provide.”
Giving time to better insights instead of trying to optimize an observability solution was exactly the shift that another customer, a cybersecurity company, wanted to achieve.
Since jumping from Datadog to Grafana Cloud, a lead SRE at the cybersecurity firm now says the SREs spend only 10% of their day managing and supporting engineers using their infrastructure because the entire team was able to easily onboard and start building alerts in Grafana. So instead of watching dashboards all day, the team can now quickly assess and troubleshoot issues when they arise.
“We’re a data-driven company; our decisions are more accurate and representative of real world scenarios versus just relying on anecdotes,” said a technical architect at the cybersecurity company. “When you’re not data-driven, decisions are very subjective and often lead to undesired results.”
5. The Grafana Labs partnership
Okay, so despite all the good things we just said, we know what you’re thinking: Migrations are a pain. It’s the devil you know, versus the devil you don’t. Or v2.0 of the old parenting adage: Don’t talk send your data to strangers.
You’re not wrong. But you also haven’t heard what companies have said about working on migrations with Grafana Labs.
The LexisNexis team collaborated directly with Grafana Labs Professional Services, which advised engineers on how to optimize queries and helped reduce response times from 30s to under a second in some use cases. Professional Services also helped to complete the LexisNexis Datadog migration in four months, achieving more than 50% savings in observability costs.
Said Neil Wilson, Director of Software Engineering at LexisNexis Risk Solutions: “We relied heavily on Grafana to help us make that transition, and it went really well.”
A cybersecurity company had a similar experience when migrating more than 20 million active series and hundreds of dashboards off of Datadog to Grafana Cloud. “The [Professional Services] team worked with us to figure out our usage, to put in limits, and to help us with the cardinality, so our experience has really improved from the beginning,” said a lead SRE.
And it’s not just the technical skills that stand out. Another customer, a point-of-sales service platform provider, benefited from Grafana courses as well as weekly office hours with Professional Services to cover migration questions.
Said an engineer embedded in the process: “One of our company tenets is to care hard, and it feels like Grafana feels that same way.”
6. Recognized observability leadership
Grafana Labs was named a Leader in the Gartner® Magic Quadrant™ for Observability Platforms* — one in a string of recognitions that shows how our company and community is playing a vital role in the area of modern software development management.
We’re also proud that Grafana Labs was named a Customers’ Choice in the Dec. 2024 Gartner Peer Insights “Voice of the Customer”: Observability Platforms.
In fact, as of Feb. 6, 2025, Grafana Labs has an Overall Rating of 4.6 out of 5 in the Observability Platforms market, based on 134 reviews on Gartner Peer Insights™, with 93% recommending our products.
Said one software developer who migrated onto Grafana Cloud from their legacy stack: “Using Grafana after using our previous observability tool is a breath of fresh air. It’s everything I want in an observability provider.”
Grafana Labs Professional Services: Datadog to Grafana Cloud migration
Grafana Labs’ Professional Services offers extensive technical expertise, having successfully guided more than 50 customers through migrations from Datadog to Grafana Labs’ solutions. Our team of trained and enabled users combines deep technical knowledge with hands-on support to ensure seamless adoption across business units and to build scalable frameworks for long-term growth.
The Professional Services team is also technically well-versed in Datadog and has successfully completed numerous large-scale migrations.
To learn more about Professional Services and how they can help you, contact your Grafana Labs rep for more information.
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Gartner® Magic Quadrant™ for Observability Platforms, Gregg Siegfried, Matt Crossley, Mrudula Bangera, Padraig Byrne, 12 August 2024
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