simplest quarter, in our the ourselves Thank executing laid out deliver you, to and review results. further initiatives us the scalable quarter we third Melanie. key cloud. successful continuing year, establishing we Good our morning, as XXXX third everyone, had and the joining thank you earlier progress as today for on metrics DigitalOcean on a
with is partnerships third the of AIML I share platform give strategic will results, how examples developer update our are continued discuss an and and In my the innovation customers, engagement our seeing tangible our ecosystem. we quarter momentum increased today, on highlight our of briefly our pace benefiting remarks with
results. XXXX recap briefly third like would I our First, financial quarter to
steady performance despite in increase remained and July Paperspace XX% with at our solid in growth AI and April difficult in the the managed price lapping from year-over-year from cloud core growth XXXX. Revenue acquisition in in comps quarter XXXX third continued hosting
We momentum for ARR our close to QX grew again products, see year-over-year. AIML where continue XXX% in demand to
growth addition, and new we year million $X end we core are and In the lower full results top saw our $X our success continue of from and our growth X as first by from delivered through go-to-market to by Having customers revenue the we million. motions. contributions customer steady end guide business the enhance strong increasing revenue quarters,
continue year-over-year XX% investments our We builders to our innovation go-to-market ahead overall revenue product and our of are drive focus and of XX% the revenue of scalers, XX% growth. majority who and total our on growing
XX% year margins manage product while costs strong accelerate adjusted AI. We maintained cash in we cloud margin guidance as our free at effectively innovation EBITDA and still to full also delivered flow have and continue to investing
and Matt will call. our this more through guidance results later details financial walk you on in
update start core cloud you by on platform. Let me our an giving computing
largest increased total in our that grew and velocity, on XX,XXX-plus revenue, continued our drive customer specifically we year-over-year that fastest-growing quarter. In our product the of focused needs scalers QX, the XX% XX% of and the cohort,
in new almost XX delivered In QX, quarter. we total, previous what we the released product in which is double features
other existing today. our We are hyperscaler are scalers accelerating features and that on cloud potential that will benefit
few provide larger efforts workloads. specifically highlights a of me that on Let now are needs the these focused these from
Internet. the a doesn't customers cloud of centers. connect period, and secure privacy availability the virtual between data isolation DigitalOcean within different via peering, short, direct resources gives private early data announced center Through or that that VPC for public X between to customers on the VPC We networking the ability create and VPCs traffic data different can peering, or strong to expose platform
GLB global based customers' GLB, customers. dynamic balancer, of all global the multiregional service our and available for or enabling is distribution scaling Our data latency enabling more availability generally edge traffic on traffic now the fail-over, applications, end center geographical load balancers. our services, of user, for prioritization, offers lower automatic load proximity of caching,
customers new We multinational are from our our thrilled product. that particularly roll deployments to directly to customers, to it out to this be benefit able all of scaler existing will with
general customers workloads. at and to for the daily to progressed protection the backups flexibility During enables customers' early we third our a additional from manage increased our quarter, daily weekly availability, backups availability giving This cadence.
backup retained automatically we platform backups, the given growth our are recent on and with our growing seeing volume was daily an storage object the most we This year-over-year. of XX% X with copies. footprint spaces, As large explicit need data
to launching droplets relevant VCPU, their memory customers density larger larger also who up CPU, scaling particularly are can that more droplet including quickly scale XX configurations optimized versus require XX general or storage workloads purpose and We're storage and with terabytes droplets, memory droplet scaler droplets. nodes. and configurations, VCPU CPU and large multiple XX our disk optimized variance terabytes horizontally These out X
platform. lot we customers simplicity also in troubleshooting This enables was Kubernetes Kubernetes' September, and monitoring forwarding, centralized their in of simplifying the applications which the mind. built In log announced management, DigitalOcean with
open few customers Kubernetes a to cluster event logs can clicks directly further Kubernetes for from from managed DigitalOcean the panel, analysis. just easily search settings the With forward
cloud-based week. for activations protection a saw malware We also net and enhanced application X,XXX introducing first new managed the solution security product within hosting by our
To capability X of on near to not customers innovations customers, we move us have our from date, we are models fastest-growing large helping seen malware the X also only positives purely us platform. All or false product meet revenue-generating but negative these malware these workloads our now hosting committed the helping rates our seen false larger managed of with contracts. needs protection usage-based from This have is protection.
this commitment an example, X-figure leader Sibu, a For cybersecurity a in customer quarter. existing signed Intelligence, Threat multiyear ours, of in
deal CPU chose optimized weeks customers our our Cyber of diligence, is cost premium coverage scale company. large new efficiency. workloads. helps for and continue workload scalability, to that and this computationally release DigitalOcean to heavy droplets leveraging was multiyear decision of by run they The And several sign petabyte due new after a the a DigitalOcean driven
Another These DigitalOcean analytics. over portfolio Traject example process engagement DigitalOcean Data, their Traject a to is bulk insights droplets, including and requires domains, also commitment robust managed Mongo retail customer They innovations and enhanced the and broad and Data to data use of XXX page e-commerce insights, volumes. DigitalOcean infrastructure including who customers. clean customers services, vast marketing, signed critical spaces, of workloads helping and real-time a to and multiyear amounts to serving is APIs reliable their platform for results great data DB, manage and scalable to search power deliver engine host migrate hyperscalers. the from product backups their
Colombia, One in Latin specific Peru customer-facing from the to in America, simplicity our Mexico, example from and logistics DO to is based the in They pricing transparent PCAP, a ride simple migrated they products, all of sharing strong support operating to workloads of model Brazil, leading and third their moved quarter. teams. due and and DigitalOcean and clouds various our
technology. increase Bid, No our opportunity our Upon for they DO with of revenue specializing to the a their is bidding of publishers example production ad real-time moved scaler scale, through online from Another platform, platform the reinforcing to in share a large-scale most our DO applications technical wallet optimizing validation customers. of hyperscaler customer
me let some AML provide the Next, updates side. on
layer reflects Our be layers. at application progress in AI value similar platform eclipsed monetization market a to technology AI and the evolve participating are of transformations and eventually layer. belief others strategy initial our infrastructure infrastructure the other today, the will in the that major in by in market opportunities we Like fashion the actively with creation
see pillars make to rapidly raw it use scale building using easy customers and But themselves and seek to platform AIML infrastructure. our differentiation our consume AI through as expertise. without GPU application This we agents requiring are Gen rather for customers to the where AI also is deep than everything platforms at innovating in our we
H-XXX made by layer, to customers. infrastructure droplets all the our At GPUs accelerated generally GPU available of we NVIDIA TensorCore
democratizing and access a leverage step ocean to can which customers of digital GPUs, achieving for customers. Now in on-demand mission AI all critical our overarching fractional is all
TensorCore also short, and experience and the DigitalOcean are for innovating tools with both providing network of NVLink Kubernetes availability take suite fabric GPU even of Mellanox operator it GPU are production for or GPU H-XXX toolkit. managed GPU a H-XXX NVIDIA making layer, operator nodes announced deployment, ready in nodes the manager nodes NVIDIA with to NVIDIA QX, NVIDIA on customers. can DOK comprehensive worker customers the and we droplets required infrastructure simpler how a examples install on Customers the platform, early the In of drivers, NVIDIA we container GPU with advantage for of DOKs
to in me example. solution and accurate Exchange tech financial more that latency They banks overall providing GPU process of Let company securely low advanced that providing the them transactions for the give blockchain-based transactions to quickly leveraging high-volume detect an experience the allows user models a infrastructure time they're processed for and payments. you power. end And machine by bank maintaining is real fraud enterprise risk learning processing DigitalOcean's are assess customers. both and Calian payments use in computational and to ensure infrastructure pay while H-XXX improving specializes
iterate to applications availability of so and them with AI select real quarter, the shape them AI product the keep value. In can early layer. at deliver Gen Next, and this platform easy that we Gen we build launched platform to new for business customers the that our
is enabling foundational able integrate a with power routing, augmented a leverage Customers AI data of agents friction-free aimed to from product or drive personalized strategy, key be with Users bases models can and foundational will towards AI customers generation RAG.
This the our models in which in software-centric with manner. to create retrieval their is to at knowledge create our AI and step their to few business this minutes. applications applications agent combine value a platform of just
company and and customer agents to a of create machine-specific machine data understood answers of a platform their planned customers' and that contacts that manufacturing large for plans documentation retrieve Cloud and is example and offers and Gen looking already a Cloud, queries. AI machines, plants leveraging data individual and their of that platform creates their manages AI Autonoma digitization to for An volumes we're each user-specific is Autonoma manufacturers. our
starting AI, built expertise engineering. data that [indiscernible] or their machine value platform just With without but learning, own AI not and proof these interactive deep is very now requiring DO's customers the data to products of to AIML deliver important their R&D to an companies for are overhead our users. Gen their cognitive It experience into to reduces doing custom internal that or in new products science projects, build AI to real data leverage business are concepts with note
talk AI third our me or a genetic the let pillar about the Finally, layer. of application strategy,
I our are their own talked AI-driven about, to create customers platform just As our using Gen AI agents.
front to also and addition that done AI innovating cloud In by are we using this by computing simplifying were further on humans. previously automating that, workflows
applications frequent available in it one, the And because wrong they staff their debugging pain to site perform is is of two, technical these set a One for their have when tasks. complex reliability number of engineers, something tasks. goes our specialized typically complex points SREs, customers don't cloud very or
using that we So building human by these point for customers to tasks this of done a to perform Gen agent some typically new out AI pain AI set SREs. by mitigate are our
it SRE using with integrating on We AI agent, internally our both this products. by and systems our cloud-based are externally
explain. me Let
almost for pinpoint the problems. SREs decisions, reducing by DO by cloud SRE of process using quickly the to on to technical AI help systems fixes is takes SRE in initial recommendations causes the time internal root are data to our causes the make incidents we -- AI XX% Based agent agent identify Internally, it including next amount data, ongoing log platform. to human AI an and leveraging our troubleshoot internal disparate enormous root from step underlying to
managed with issues apply fix. support thousands this and mission-critical integrated then have customer a SRE product, the happen they into agent the service This Today, just websites. but platform, of hundreds for is all engineers host cause and when digital to to Externally, not of root debug platforms. Ocean we applications, on which across AI hosting true work our cloud-based
affected, can their and a during be job time-consuming not even can This be offline. which websites if business
to into jumps agent detection issues due service any crawlers, gather bot SRE insights of degradation real thereby and on these investigate to common resolution recommendations provide AI upon attacks aggressive new time denial forth like so and action significantly. reducing Our how fix the to to performance time of issues and
few a encouraging, in customers we very working started are just Our results testing have and early with availability mode.
and up by QX. our models. users with AI platform Face a Face open strategy, source Hugging new learning build, partnership the train science door strategic out a leading we is and deploy Hugging in Rounding machine opened helps front launching that open
now popular TensorCore third-party simplicity As users of through a deployable GPU GPUs. result by to performance inferencing of and easily and this models quickly offers the partnership, most on DigitalOcean droplets, X-click models H-XXX droplets model GPU deploy NVIDIA the optimal with allowing accelerated
This Hugging simplifies ] the most performance. partnership it the use easier complexity DigitalOcean trillion more popular deployment integrated source the these models offering make X models DigitalOcean users and and for enabling AI/ML the [ open discover for platform. GPU will droplets, to deployment natively of has phase superior fast and as The hugging Face optimize than
managed partnerships the partnerships leading flight, seamlessly a the to build to Netlify applications DigitalOcean development already also without doors to connect leading channels, new complexities their with shape have of the and In ecosystem and offering improve These our addition our a additional various in announcements, through scale developers tools in to front QX, customers players with we product including highlight also help their Netlify, other we mode efforts will partnership that product-led with to enable Web augment durable infrastructure. MongoDB, in applications all managing our offerings. right growth to our platform announced new
internal open OctoberFest, a are October, event I'm DigitalOcean developer of from events. also addition evolved premier highlight excited the and material to engagement to community which largest making In has being hosted at progress source the an with Hackaton the the XXth we now X with of we community. renewed
open XXX projects. run over than This countries XX,XXX from source XXX events more developers XX,XXX year, in participated contributed community and to
also reinforces our broad-based Beyond to effort Hacker developers This conferences. community developer of and DigitalOcean's more engagement ecosystem. than a for number XX participated hosted community DigitalOcean and we in Fest, meetups industry community ongoing AIML
helping encouraged shoots form scaler great particularly shipping rapidly grow of in multiyear DO green as and of AI wins, and engagement am software-centric We're also I AI it to real-world see platform. X We're using the the our layers: from expand. progress platform starting migrations our deployment product the on the making closing, In their investments to as customer customers hyperscalers, commitment applications. products including continue the AI by each platform the of vision these towards our is and by customer from infrastructure, and innovation cloud builder on in businesses contracts strides
we will to We quarters and continue our accelerate seek on the to largest to focus in fastest-growing customer cohorts come. as growth
of more which XXXX, targeting Before I call Day to our hosting we March well long-term will be Investor are an share I'm Matt, outlook. on City, on currently New metrics share and and progress detail early over in more including very York a strategy, excited as as view calendar to our long-term QX will turn in late or we we financial the our that
call and over now outlook the details Thank additional Matt you. our on results provide some QX who our now will to CFO, XXXX. I financial hand will for Steinfort, our
