SentinelOne partners with AWS to enhance AI-powered cloud security
The AWS Security Hub is designed to identify, prioritise, and support the remediation of critical cybersecurity risks. It integrates information from sources such as threat detection and vulnerability management, and enhances these signals with visualisations, natural language summaries, and automated response actions. The goal is to help organisations strengthen their security posture, make informed decisions, and reduce potential operational disruption.
SentinelOne's partnership with AWS on the Security Hub initiative means that enriched and correlated security findings within AWS Security Hub are now able to be ingested directly into SentinelOne's Singularity Platform. This platform supports AI-enabled detection and response capabilities, leveraging SentinelOne's Purple AI for automated security workflows through its Hyperautomation features. "Co-building with AWS is one of the most valuable ways we plan to help customers meet their evolving security goals," said Ric Smith, President of Product, Technology, and Operations at SentinelOne. "Our partnership with AWS Security Hub brings deep integrations that deliver the clarity, speed, and automation security teams need to defend complex cloud environments."
The collaboration is an extension of a long-standing relationship between SentinelOne and AWS focused on advancing AI-powered security frameworks for businesses using AWS. Over the course of their partnership, the companies have co-developed a range of integrated solutions, with the current integration covering more than 20 AWS services. This enables organisations to streamline their security operations, enhance visibility across cloud assets, and improve defences against emerging threats.
According to SentinelOne, working alongside AWS on shared security solutions allows the companies to innovate in areas that address the most demanding security requirements in the cloud computing sector. As a strategic AWS partner, SentinelOne states it is committed to ongoing development work with AWS to bring new features and joint offerings to market.
SentinelOne's Singularity Platform, which now integrates findings from AWS Security Hub, provides customers with AI-driven threat detection, response, and automation capabilities. This is designed to assist security teams in handling complex cloud environments efficiently and to support enterprises in keeping ahead of evolving cyber risks. SentinelOne also says that these combined offerings enable customers to continue growing their businesses on AWS infrastructure while maintaining protections for critical workloads.
SentinelOne has previously highlighted a focus on supporting secure cloud migrations for AWS customers. The company has described the AWS Marketplace as a key channel for distributing its Singularity AI SIEM offering, which it claims to be its fastest-growing product. SentinelOne's collaboration with AWS includes a range of technical integrations and shared cloud security initiatives intended to assist customers as they migrate to and operate within the AWS cloud environment.
The AWS Security Hub, with support from launch partners such as SentinelOne, offers an environment for consolidating security data, automating responses, and potentially reducing the time and resource investment required to protect cloud applications and infrastructure. The integration with SentinelOne's technology extends this capability further by tying into AI-powered response systems designed for rapid and automated threat management.
The companies have indicated that their partnership, encompassing over 20 AWS services, enables enterprises to focus on developing their businesses with the assurance that cloud security operations are backed by joint research and technological advances from both AWS and SentinelOne.
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Our SaaS platform integrates and automates infrastructure monitoring, application performance monitoring, log management, user experience monitoring, cloud security and many other capabilities to provide unified, real-time observability and security for our customers' entire technology stack. Datadog is used by organisations of all sizes and across a wide range of industries to enable digital transformation and cloud migration, drive collaboration among development, operations, security and business teams, accelerate time to market for applications, reduce time to problem resolution, secure applications and infrastructure, understand user behavior, and track key business metrics. Forward-Looking Statements This press release and the earnings call referencing this press release contain 'forward-looking' statements, as that term is defined under the federal securities laws, including but not limited to statements regarding Datadog's strategy, product and platform capabilities, the growth in and ability to capitalise on long-term market opportunities including the pace and scope of cloud migration and digital transformation, gross margins and operating margins including with respect to third-party cloud infrastructure hosting costs, sales and marketing, research and development expenses, net interest and other income, cash taxes, investments and capital expenditures, and Datadog's future financial performance, including its outlook for the third quarter and the full year 2025 and related notes and assumptions. These forward-looking statements are based on Datadog's current assumptions, expectations and beliefs and are subject to substantial risks, uncertainties, assumptions and changes in circumstances that may cause Datadog's actual results, performance or achievements to differ materially from those expressed or implied in any forward-looking statement. The risks and uncertainties referred to above include, but are not limited to (1) our recent rapid growth may not be indicative of our future growth; (2) our history of operating losses; (3) our limited operating history; (4) our dependence on existing customers purchasing additional subscriptions and products from us and renewing their subscriptions; (5) our ability to attract new customers; (6) our ability to effectively develop and expand our sales and marketing capabilities; (7) risk of a security breach; (8) risk of interruptions or performance problems associated with our products and platform capabilities; (9) our ability to adapt and respond to rapidly changing technology or customer needs; (10) the competitive markets in which we participate; (11) risks associated with successfully managing our growth; and (12) general market, political, economic, and business conditions including concerns about trade policies, tariffs, reduced economic growth and associated decreases in information technology spending. These risks and uncertainties are more fully described in our filings with the Securities and Exchange Commission (SEC), including in the section entitled 'Risk Factors' in our Quarterly Report on Form 10-Q for the quarter ended March 31, 2025, filed with the SEC on May 7, 2025. Additional information will be made available in our Quarterly Report on Form 10-Q for the quarter ended June 30, 2025 and other filings and reports that we may file from time to time with the SEC. Moreover, we operate in a very competitive and rapidly changing environment. New risks emerge from time to time. It is not possible for our management to predict all risks, nor can we assess the impact of all factors on our business or the extent to which any factor, or combination of factors, may cause actual results to differ materially from those contained in any forward-looking statements we may make. In light of these risks, uncertainties and assumptions, we cannot guarantee future results, levels of activity, performance, achievements, or events and circumstances reflected in the forward-looking statements will occur. Forward-looking statements represent our beliefs and assumptions only as of the date of this press release. We disclaim any obligation to update forward-looking statements. About Non-GAAP Financial Measures Datadog discloses the following non-GAAP financial measures in this release and the earnings call referencing this press release: non-GAAP gross profit, non-GAAP gross margin, non-GAAP operating expenses (research and development, sales and marketing and general and administrative), non-GAAP operating income (loss), non-GAAP operating margin, non-GAAP net income (loss), non-GAAP net income (loss) per diluted share, non-GAAP net income (loss) per basic share, free cash flow and free cash flow margin. Datadog uses each of these non-GAAP financial measures internally to understand and compare operating results across accounting periods, for internal budgeting and forecasting purposes, for short- and long-term operating plans, and to evaluate Datadog's financial performance. Datadog believes they are useful to investors, as a supplement to GAAP measures, in evaluating its operational performance, as further discussed below. Datadog's non-GAAP financial measures may not provide information that is directly comparable to that provided by other companies in its industry, as other companies in its industry may calculate non-GAAP financial results differently, particularly related to non-recurring and unusual items. In addition, there are limitations in using non-GAAP financial measures because the non-GAAP financial measures are not prepared in accordance with GAAP and may be different from non-GAAP financial measures used by other companies and exclude expenses that may have a material impact on Datadog's reported financial results. Non-GAAP financial measures should not be considered in isolation from, or as a substitute for, financial information prepared in accordance with GAAP. A reconciliation of the historical non-GAAP financial measures to their most directly comparable GAAP measures has been provided in the financial statement tables included below in this press release. Datadog defines non-GAAP gross profit, non-GAAP gross margin, non-GAAP operating expenses (research and development, sales and marketing and general and administrative), non-GAAP operating income (loss), non-GAAP operating margin and non-GAAP net income (loss) as the respective GAAP balances, adjusted for, as applicable: (1) stock-based compensation expense; (2) the amortisation of acquired intangibles; (3) employer payroll taxes on employee stock transactions; (4) M&A transaction costs; (5) amortisation of issuance costs; and (6) an assumed provision for income taxes based on our long-term projected tax rate. Non-GAAP financial measures prior to April 1, 2025 have not been adjusted for M&A transaction costs, as such costs were not material to our results of operations in such prior periods. Our estimated long-term projected tax rate is subject to change for a variety of reasons, including the rapidly evolving global tax environment, significant changes in Datadog's geographic earnings mix, or other changes to our strategy or business operations. We will re-evaluate our long-term projected tax rate as appropriate. Datadog defines free cash flow as net cash provided by operating activities, minus capital expenditures and minus capitalised software development costs, if any. Investors are encouraged to review the reconciliation of these historical non-GAAP financial measures to their most directly comparable GAAP financial measures. Management believes these non-GAAP financial measures are useful to investors and others in assessing Datadog's operating performance due to the following factors: Stock-based compensation. Datadog utilises stock-based compensation to attract and retain employees. It is principally aimed at aligning their interests with those of its stockholders and at long-term retention, rather than to address operational performance for any particular period. As a result, stock-based compensation expenses vary for reasons that are generally unrelated to financial and operational performance in any particular period. Amortization of acquired intangibles. Datadog views amortisation of acquired intangible assets as items arising from pre-acquisition activities determined at the time of an acquisition. While these intangible assets are evaluated for impairment regularly, amortisation of the cost of acquired intangibles is an expense that is not typically affected by operations during any particular period. Employer payroll taxes on employee stock transactions. Datadog excludes employer payroll tax expense on equity incentive plans as these expenses are tied to the exercise or vesting of underlying equity awards and the price of Datadog's common stock at the time of vesting or exercise. As a result, these taxes may vary in any particular period independent of the financial and operating performance of Datadog's business. M&A transaction costs. Datadog views acquisition-related expenses, such as transaction costs, as costs that are not necessarily reflective of operational performance during a period. In particular, Datadog believes the consideration of measures that exclude such expenses can assist in the comparison of operational performance in different periods which may or may not include such expenses. Amortisation of issuance costs. In June 2020 and December 2024, Datadog issued $747.5 million of 0.125% convertible senior notes due 2025 and $1.0 billion of 0% convertible senior notes due 2029, respectively. Debt issuance costs, which reduce the carrying value of the convertible debt instrument, are amortized as interest expense over the term. The expense for the amortization of debt issuance costs is a non-cash item, and we believe the exclusion of this interest expense will provide for a more useful comparison of our operational performance in different periods. Additionally, Datadog's management believes that the non-GAAP financial measure free cash flow is meaningful to investors because it is a measure of liquidity that provides useful information in understanding and evaluating the strength of our liquidity and future ability to generate cash that can be used for strategic opportunities or investing in our business. Free cash flow represents net cash provided by operating activities, reduced by capital expenditures and capitalized software development costs, if any. The reduction of capital expenditures and amounts capitalized for software development facilitates comparisons of Datadog's liquidity on a period-to-period basis and excludes items that management does not consider to be indicative of our liquidity. Operating Metrics Datadog's number of customers with ARR of $100,000 or more is based on the ARR of each customer, as of the last month of the quarter. We define the number of customers as the number of accounts with a unique account identifier for which we have an active subscription in the period indicated. Users of our free trials or tier are not included in our customer count. A single organisation with multiple divisions, segments or subsidiaries is generally counted as a single customer. However, in some cases where they have separate billing terms, we may count separate divisions, segments or subsidiaries as multiple customers. We define ARR as the annualised revenue run-rate of subscription agreements from all customers at a point in time. We calculate ARR by taking the monthly recurring revenue, or MRR, and multiplying it by 12. MRR for each month is calculated by aggregating, for all customers during that month, monthly revenue from committed contractual amounts, additional usage, usage from subscriptions for a committed contractual amount of usage that is delivered as used, and monthly subscriptions. ARR and MRR should be viewed independently of revenue, and do not represent our revenue under GAAP on a monthly or annualised basis, as they are operating metrics that can be impacted by contract start and end dates and renewal rates. ARR and MRR are not intended to be replacements or forecasts of revenue.
