Thousands of customers love & trust Datadog
Shifting to DevOps promises accelerated development cycles and enhanced agility in responding to market needs. However, this transition can require a great deal of change for an organization, which can be difficult and time-consuming to adjust to, ultimately slowing down a full DevOps adoption. Datadog supports organizations moving to DevOps with tailored workflow, collaboration, and tooling that works out-of-the-box. As organizations begin to use Datadog, they start to fit their work into many DevOps processes, providing the scaffolding for this notable organizational change.
“We needed to make it such that a bunch of different teams could move independently and make their own decisions rather than centralizing a lot of decision making and operations through a single team.”
– Steven Verleye, Manager - Infrastructure Engineering, BazaarVoice
Change initiatives can be difficult for any company to implement, but DevOps workflows in particular affect not only processes but also team structure and tooling, and often require existing employees to learn new skills to complete these new workflows. Organizations frequently find that DevOps adoption is far slower than expected as employees develop these skills, form relationships with team members they hadn’t previously worked with, pick new tools, and change their processes. Datadog works to support DevOps adoption by introducing tailor-made solutions to fill in the gaps that organizations experience. Datadog’s integrations are built with domain-knowledge and not only collect handpicked data, but also feature out-of-the-box dashboards that give any user, regardless of their level of understanding of that component, instant insight into performance health. Certain integrations feature bi-directional syncs, allowing workflow steps taken in Datadog to enact the appropriate change in the other tool. And Datadog’s collaboration features are strategically placed within issue escalations and ML-identified problems to ensure that all team members that should be working on an issue are indeed made aware of that work.
One of the central DevOps principles is to automate as much as possible in order to reduce manual work and accelerate the flow of information. While DevOps automation can speed up workflows and make a number of processes more efficient, it can also lead to unexpected consequences as systems interact in unplanned ways, or when the automation tool itself suffers from a performance issue or misconfiguration. Datadog ensures that automation within DevOps processes will continuously perform as expected, and offers vendor-supported integrations with commonly used DevOps automation tools. Out-of-the-box dashboards for these tools are available to immediately show if there are issues occurring with the tools themselves. Importantly, every time an automated action runs, Datadog notes this occurrence as an event, which can then be correlated with performance metrics from the application and infrastructure to understand how specific automated actions impact the performance of application components.
Because DevOps processes cross over multiple functions and break silos, teams that adopt DevOps have the need to see not only the systems they work with, but also the upstream and downstream services they interact with. This requires unrestricted access to performance metrics and other data from all infrastructure systems, the application itself, and the front end that end users are working with. Datadog has been purpose-built to allow for universal visibility within each account. Teams working with Datadog are able to view the logs, traces, and metrics from all application and infrastructure components that are integrated in their accounts, and can create dashboards, alerts, and run analytics on the data — whether it is originating from the systems they work on or from those of other teams. Datadog also includes federation capabilities so that multiple instances can be created in an account so each independent division of a company can have instance-wide access, but the entire company can combine data from all divisions when needed.
As silos break and new cross-functional teams are formed to undertake DevOps workflows, employees who might not have known each other previously need to work together on a daily basis. The systems that these teams operate are complex and dynamic, making it critical for all team members to be, literally, on the same page as issues are investigated and data is analyzed. Datadog allows for entire organizations investing in DevOps adoption to easily evaluate data in the same context, making collaboration and information sharing an automatic impulse when undertaking a task. Datadog integrates out-of-the-box with ticket tracking, chat, and alert routing tools so that when data is shared through these commonly used systems, all additional metadata is included in the outbound communication and comments from these other systems can be sent back into Datadog. Comments in Datadog are saved and searchable for more than a year. Datadog features robust annotation, snapshotting, and commenting capabilities as well as a notebook capability so that any Datadog user can ad-hoc document and notify other users and distribution lists about conditions that they observed right on the data — all other users can then jump to that exact point in time. Ultimately, Datadog becomes an easily searchable and shareable system of record for all data on system performance and changes, as well as employee conversations regarding that data.