Faster Innovation and Digital Transformation with 

InfluxDB Cloud on Google Cloud  

 Cloud services is a fast-growing market and an attractive option for organizations that would like to abstract computational infrastructure and domain expertise from their application development and operational concerns. Customers can then concentrate efforts on implementing applications with advanced business logic and differentiation while aggregating best-of-breed services to bring competitive solutions to market quickly. As appealing as that may be, cloud services face their own challenges. For instance, regulatory requirements on data can be showstoppers — or at least prolong the sales process — for certain implementations. Besides compliance, observability of the entire application environment and data availability for connected intelligence of frameworks and workflows may also steer the customer’s decision when opting for cloud and/or on-prem deployments.  

Google’s partnership with InfluxData to offer InfluxDB Cloud on Google Cloud (formerly known as GCP) gives customers options, complete visibility and the necessary flexibility in data governance to address their challenges with confidence. Certainly, eliminating the infrastructure burden for IT operations while keeping customers in control of their assets is a great value proposition. Nonetheless, benefits don’t stop there. Google and InfluxData are working together to deliver the most streamlined and painless time series database solution. InfluxDB Cloud as a part of the Google Cloud marketplace brings the unification of procurement, billing and support along with the entire Google Cloud menu of services. Customers will get even more from this partnership, a time series data management and analytics platform fully integrated with Google Cloud solutions’ data pipelines and data sources. In other words, a network of data sharing where all time-stamped data acquired and stored can be used to provide visibility into the entire application stack. This enables innovative applications with better user-experience, more precise prediction modeling, and an entire new horizon of automated services.   Together, Google and InfluxData are bringing to the cloud services marketplace the tactical and strategic benefits from a global, trusted, enterprise-grade supported infrastructure platform where all time series data can be managed and leveraged. By doing so, this partnership is providing a place where fast innovation and digital transformation can be achieved.      

 

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See below a diagram illustrating InfluxDB Cloud services integrated with GCP marketplace:  

 

A platform for all time series data and analytics   The presence of InfluxDB Cloud on Google Cloud means that customers have ready-to-use access to the industry’s leading time series and data analytics platform for real-time decision making. InfluxDB is easy and simple — your data can start producing value on day-1.   In addition to unified procurement processes, billing and experience provided by Google Cloud services, having InfluxDB as part of the menu of the integrated application infrastructure and services is powerful for customers migrating to data-driven workflows. That is because InfluxDB is more than a purpose-built time series database — it is a platform for ingesting, processing, visualizing and analyzing time series data — the central nervous system for acquiring and serving time series data to and from various application systems and frameworks.      

 

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With InfluxDB Cloud on GCP, customers can address a wide range of use cases:   

  Time series feed multiple frameworks such as monitoring dashboards and incident management to predictability modeling and automation — like machine learning (ML) and Artificial Intelligence (AI). Therefore, having a purpose-built time series platform that can handle cloud-scale data pipelines (batch and streaming) ready and open to receive and render your time-stamped data is convenient and strategic. InfluxDB Cloud will keep your digital time series assets reusable and free to serve your applications and workflows.   See below a diagram of InfluxDB platform architecture: 

 

 

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The roles of monitoring in Cloud Services: SLA cross-check, observability for timely actions, and business insights for continued success  Since monitoring involves a time component, it requires the collection, processing and visualization of time series data. As organizations become data-driven — using applications in containerized environments, fragmented in tiers and layers of abstraction and cloud services — monitoring use cases grow at an accelerated pace. So does the volume of time series data collected. The InfluxDB time series platform is a key component in any cloud services marketplace as it provides the means to address monitoring use cases of cloud deployments cost-effectively and at cloud scale.   SLA cross-check  At the forefront of the cloud services’ value is the Service Level Agreement (SLA), which constitutes some level of quality commitment on what is being sold as a service. Compliance to SLAs, undoubtedly, cannot be achieved only by a self-assessment done by the cloud provider in question. Benchmark reports show that there are different levels of stability experienced in cloud services from different cloud providers, as well as varying performance.   

 

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Common-sense guides us to trust, but verify. Therefore, organizations must implement SLA checks to monitor if the services provided meet the agreed-on quality terms. Implementing SLA checks requires identifying Service Level Objectives (SLOs) to measure and monitor — such as maximum total downtime in a defined time frame, maximum mean time to recovery (MTTR), platform crashes, service anomalous delay, etc. Finally, these checks require defining the metrics and events to be collected that would enable monitoring SLOs. Therefore, customers must have means to collect the necessary data — resource and performance metrics as well as log and event data — in order to properly monitor the services provided.   Holistic observability of system health, application behavior and user experience  In the same way that one must monitor SLAs from cloud providers, it is also necessary to stay on top of state, status and behavior of your own applications to ensure that the experience delivered is satisfactory. At the core of a stellar user experience is the ability to perform preemptive monitoring in order to take preventive action. Therefore, it is fundamental to maintain full visibility into metrics and events across the entire application stack, from the actual resources where they run on to virtualization layers (such as VMs, containers and Kubernetes), cloud services tiers (databases, AAA services, etc.), as well as networks connecting applications and services.  Latency, errors, exceptions, crashes and disruptive events, or pressing load such as query/secs, happen in any real-world application environment. How often issues arise, what systems go down, how quickly root-cause can be identified, and recovery time duration determine the extent of the impact on user experience. But you don’t want to wait until customers complain to find out what is occurring in your application environment. You need to act preemptively regardless of who is to blame for the issue. You also need to quickly identify root-cause to reduce MTTR by leveraging your time series data from multiple sources to correlate performance issues with events (such as, errors, failures, exceptions, etc.). Observability of all layers and tiers of your cloud services is what enables effective decision-making.  Business KPIs monitoring  Monitoring key indicators at the business level is important not only for business audiences but also for response teams. High-level indicators — tracking success of critical transactions such as number of orders or forms successfully submitted — improve visibility over relevant infrastructure and application metrics regarding subtle degradations that have direct business impact. Otherwise, such degradations get lost within the massive volumes of metrics collected. Individual metrics and event measurements are too granular, and in isolation, don't deliver the bigger picture about potential issues or opportunities.   Analyzing composed indicators, correlated with log events and enriched with metadata to extract critical business insight is an important use case supported by time series platforms such as InfluxDB. By also providing a powerful analytics engine, InfluxDB can assist customers in prediction models applied to business intelligence, processes and cost optimization.   The advantages of elastic resources, flexible usage-based pricing, global reach and ease of use of serverless services are compelling enough reasons to adopt cloud services. Nonetheless, monitoring the quality of service received, resources consumed and performance of all services, systems and 

 

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applications, as well as business indicators through a single ‘pane of glass’ — a unified view of critical transaction parameters, metrics, events and logs — is no longer optional but necessary.   Cloud monitoring personas  Lack of visibility into cloud services’ internal operations is one of the top customer pain points — and for good reason. Sustaining crash-free, high-performing cloud service cannot be taken for granted; one must measure and monitor the quality of all involved elements. There are multiple layers of audiences and stakeholders that consume information differently and for different purposes. Here are some examples of segmentation for different cloud personas:  

● SLAs enforcement, compliance and cost control drive KPIs for budget owners at the executive level. 

● Compliance and security drives KPIs for budget owners in executive and security teams. ● Application performance and user experience drive KPIs for project and/or budget owners in 

devops teams. ● Navigation of metrics, logs and events for troubleshooting drives interest from response teams. ● Business intelligence drives composed, enriched and correlated KPIs for line of business 

stakeholders.  In order to have the necessary data and metadata to provide the most appropriate information and visualization model for the various personas, it is necessary to fully observe quality and cost-efficiency of service utilization, as well as the performance of applications, services and business-critical transactions — and to be able to use this observation data to devise analytical models for predictability, automation and high-value business insights. 

InfluxDB Cloud integration with Google Cloud Services  

InfluxDB Cloud is a serverless time series data platform-as-a-service. Although monitoring of application environments in the cloud and on-premises is a compelling and common use for time series, there is much more that a time series data platform like InfluxDB Cloud offers.   Time series powers the development of modern applications and enables new and more targeted services by unveiling the particular ways users behave and consume services. It also provides a common dimension through which multiple measurements can be correlated to reveal how different aspects impact an outcome. InfluxDB enables all these capabilities preemptively when used for machine learning (ML) and artificial intelligence (AI). Nonetheless, the first step is to collect the data.  InfluxDB’s plugin-based (200+) collector agent Telegraf — together with its RestAPI, client libraries, and real-time streaming engine — provide a wide foundation for integrations with legacy and modern applications and data pipelines. To highlight some important monitoring and data processing use cases for InfluxDB Cloud on GCP, below let’s review some of the popular Telegraf plugins to consider with Google Cloud:  

 

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● Stackdriver integration: The Telegraf Stackdriver plugin collects metrics, events and metadata from 40 different Google Cloud services and stores them in InfluxDB for dashboarding with Chronograf (or Grafana) and analytics operations using Flux (new scripting and query language) for InfluxDB. Telegraf can also send data to Stackdriver via the Telegraf Stackdriver output plugin.   

● PubSub integration: Telegraf can be configured to a pull or push subscription on Google Cloud Pub/Sub via the PubSub Plugin and PubSub Push plugin respectively. Telegraf can also send data from InfluxDB to be published to a topic on Google Cloud Pub/Sub service using its Pubsub Output Plugin. From Cloud Pub/Sub the data can be consumed in the Google Cloud ecosystem, for instance, Stackdriver Logging, Dataflow, BigQuery, BigTable, Cloud Storage, App Engine, Compute Engine, and so on.  

● Google Kubernetes Engine (GKE) & Anthos integration: InfluxDB platform provides a comprehensive solution to fully monitor Kubernetes components: control plane, add-on services, and node clusters. Telegraf Kubernetes plugin talks to Kubelet API and gathers metrics on pods and containers running on a host. Telegraf Kube Inventory plugin gathers metrics derived from the state of Kubernetes resources at cluster level such as daemonsets, deployments, nodes, pods, containers etc. And there’s the Telegraf Prometheus plugin, which gathers metrics from applications and services exposing metrics in Prometheus format (/metrics endpoint). Telegraf can be deployed as a DaemonSet in the same fashion as Prometheus’ Node Exporter to collect metrics at node level, or as a sidecar collecting metrics and events from applications and services running on containers in a pod. All metrics and logs from Anthos application platform collected by Stackdriver monitoring and logging services can be sent to InfluxDB Cloud for unified visualization, root-cause analysis and alerting.  

● Cloud Build integration: Telegraf can monitor containers used by Google Cloud Build with Docker plugin and Docker Log plugin. 

 ● Compute Engine: Telegraf can monitor virtual machines spun up by Google Compute Engine, 

using its monitoring plugins to capture metrics for server CPU, disk, memory, network, processes, swap, and system uptime. Telegraf can also use its vast menu of application plugins to monitor also the custom applications running on GCP virtual machines as well as common application components such as NGINX, Apache Web server, MySQL, PostgreSQL, Cassandra etc. 

 ● IoT Core: Telegraf integrates with Google IoT Core via Pub/Sub push integration, from which it 

can ingest metrics from devices and sensors. Additionally, Telegraf can consume MQTT topics, using its MQTT input plugin. Telegraf can also output data to MQTT. 

 ● Bigtable, BigQuery: Flux can import data from other SQL and noSQL data sources, and do 

joins. Flux is a new open-source data scripting and querying language, designed for working with time series data. 

 InfluxDB Cloud on GCP makes it easy and painless to become a data-centric organization, while keeping the organization’s data fluid, enrichable and increasingly valuable.   

 

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 See below a diagram of how InfluxDB offers holistic observability on-premises and in the cloud: 

 

InfluxDB Cloud time series data flow integration  

As a general direction, cloud service providers must offer not only a menu of services but also options, flexibility and full data flow integration among applications and services. InfluxData’s partnership with Google Cloud services delivers on all these fronts. With open APIs and an open-source time series database platform, customers are well-served in gaining the ability to leverage data to bring competitive solutions to market while improving business efficiency and effectiveness.   The fastest way to achieve the envisioned data-driven utopia is to enable the workforce — by putting within their reach the tools and means to start using time series data to monitor and guide their efforts. This enablement path should be embraced not only by the usual time series personas (DevOps) but also by business stakeholders and teams in all areas. As these personas embrace data to detect issues, unveil trends and measure success, demand for time series data collection, visualization and analytics will continue to rise.   That is where InfluxDB Cloud service on Google Cloud will make a difference in the journey. Easy-to-start and expand to various use cases, it empowers anyone to take the first step. Whatever 

 

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time-stamped data organizations would like to collect, store, process, monitor and act on — whether coming from devices, systems or other Google cloud services — can be sent to InfluxDB Cloud with minimal effort.   InfluxDB Cloud integrations with Google Cloud services also enable an application network to be established, where data flows through applications creating a collective intelligence that can be leveraged to serve multiple frameworks and workflow automation. See below integrated data flow diagram:   

  With InfluxDB Cloud on Google Cloud, customers will not only have options and flexibility but also a critical component for data-driven organizations: interoperability. Google Cloud provides an environment with data flow integrations to form a network of data consumers, via which applications and analytics frameworks can be served for multiple stages of value extraction. For instance, InfluxDB Cloud can ingest and render time series data for real-time or historical analysis from and to various applications and tools. It serves as the acquisition sink to which time series pipelines (RestAPI batch, telemetrics streaming, messages bus/queues, etc.) can send data. Operations, transformations and analytical processing can be performed on the data before being presented to its consumers: IT managers, operation and SRE teams, developers, business stakeholders, and C-level executives.  

 

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Keeping cloud services customers empowered with options and 

open source solutions 

As competition increases, cloud providers will have to find ways to avoid commoditization and churn by adding high-value functionalities while further engaging customers through additional services. However, different from past practices, revenue growth and “stickiness” will not come from keeping customers and data locked. On the contrary, customers are increasingly averse to silos, inflexibility for gradual growth, lack of visibility, and certainly, the increasing costs and complexity of licensing plans.   Compelling cloud services marketplaces will primarily provide customers with options to find the most cost-effective solution for their use cases in the short and long run. That includes a menu of open source solutions as well as options for multi-cloud, on-premises, and even edge deployments. Options give customers flexibility to balance cost, comply with data governance policies and optimize performance of their applications, while strengthening the cloud provider’s position as a customer-centric marketplace.  InfluxDB Cloud adds to Google Cloud services the level of flexibility, visibility and forethinking demanded by the current pace of development and market competitiveness. Customers have within the reach of a click a platform that is ready for common and custom time series use cases. With open APIs and options for hybrid (cloud and on-prem) deployments, InfluxData also empowers customers to find the right data management model that addresses regulatory requirements, while keeping up with market speed.   Google Cloud customers have the option and freedom to use InfluxDB in different deployment types:   

● InfluxDB Cloud — serverless (fully managed service including updates, upgrades, security compliance, and HA) with elastic scalability on multiple cloud service marketplaces with a free entry tier. InfluxDB Cloud is offered on Google Cloud and AWS.  

● InfluxDB Enterprise (infrastructure managed by the customer) — supported clustered deployment of instances of InfluxDB in the cloud or on-premises with HA and horizontal scalability. 

● InfluxDB OSS — free single node deployments without enterprise-grade support, security and access controls.  

 See below InfluxData’s offerings and deployment options:  

 

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 Each type of deployment has its use cases, and customers can choose the deployment that serves their unique needs from PoC projects and development to organization-wide data management planning.   InfluxData offers an unified API for all InfluxData offerings: InfluxDB Cloud, InfluxDB Enterprise and InfluxDB OSS. Customers can move their data from open source InfluxDB OSS to InfluxDB Enterprise to InfluxDB Cloud as needed to meet their objectives. With InfluxDB, meeting compliance requirements and cost balancing is not only possible but made easy. All, ingestion, query, storage and visualization, can be done programmatically via a unified API without operational burden.  

Embracing serverless cloud solutions that are also open source is important not only for flexibility and vendor lock-in avoidance but also for enabling future innovation. For instance, InfluxDB improvements are made by a vast community of contributing developers in addition to InfluxData’s own development team. New features and functionalities are added at a much faster pace. As soon as they are integrated with the serverless platform, they become instantaneously available to customers.  InfluxDB Cloud on Google Cloud, beyond the advantages of InfluxDB platform, provides the easiest onboarding experience to existing Google Cloud customers, and some practical aspects such as the ones below can really streamline the process: 

 

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 ● Pre-qualification with regards to procurement, policy compliance and infrastructure security 

diligence (without such pre-qualification, customers could face barriers to adoption or process slowdown) 

● Google’s inclusion of InfluxDB in the menu of services for Google Cloud credits, which makes time series adoption painless and easy 

Painless scaling, procurement, unified billing along with integrated cloud services; democratization of data could not be made easier. 

 

InfluxData is part of Google’s open source partner ecosystem. With this partnership, Google shows its commitment to enabling faster innovation and digital transformation by providing InfluxDB customers with a highly available, secure and flexible platform to thrive on. Furthermore, InfluxDB Cloud on Google Cloud customers will benefit from the convenience of unified billing, single user experience and procurement with standard Google Cloud credits. But the compelling reasons for customers to adopt InfluxDB Cloud on Google Cloud are not limited to these. InfluxDB Cloud on Google Cloud also allows customers to:  

● Unify, enrich, correlate and cross-check StackDriver Monitoring data of Google Cloud services (Compute Engine, App Engine, GKE, networking, Cloud PubSub, etc.) with health, state, performance metrics, logs issues, error and exceptions events of workloads and applications collected via Telegraf 

● Keep a network of data that feeds multiple frameworks and provides a continuous chain of value creation 

● Generate business insights and enable data-driven decisions for immediate action as well as higher predictability accuracy 

 

 InfluxData functional architecture 

 

 

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InfluxDB Cloud on Google Cloud is an important step taken by Google and InfluxData to help customers innovate faster by providing a ready-to-start platform for time series data. A centralized platform for data management, elastic resources, flexible spending, global reach and easy-to-use serverless services is a strong force driving adoption of cloud services at different organizational levels. Time series users can now start using InfluxDB Cloud directly integrated with Google Cloud services and data flows for ingesting, storing, analyzing, visualizing and acting on time series data.   Therefore, InfluxData partnership with Google is a critical component to Google Cloud services to manage all types of time series data, overcoming operations skill gap, cost and lock-in concerns, while allowing organizations to concentrate on transforming their skillset towards using data into their processes and workflows. InfluxDB Cloud on Google Cloud facilitates user access to data, addressing the needs and concerns of all constituencies, and providing the flexibility to accommodate regulatory requirements as well as operational and business goals.  By offering a comprehensive menu of solutions while establishing partnerships in the open source space, Google is positioned to be a good marketplace choice for the digital transformation journey. And as organizations start considering a time series strategy for their IT and applications development roadmap and architecture.   Time series data is a generous source of insights. This fact is driving innovative organizations to adopt the InfluxDB purpose-built platform in order to fully realize time series rewards. In partnership with Google, InfluxData offers InfluxDB Cloud on Google Cloud, an empowering and enabling tool within reach of all stakeholders and consumers of time series data. So, focus on extracting value from your data, and let us take care of the rest.    

 InfluxData: the platform of choice for all metrics and event workloads 

  

  

 

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InfluxData is committed to bring to its customers flexibility and options. InfluxDB Cloud is currently available on GCP, AWS and, in the near future, also on Microsoft Azure.  

About InfluxData 

InfluxData is the creator of InfluxDB, the open source time series database. Our technology is 

purpose-built to handle the massive volumes of time-stamped data produced by IoT devices, 

applications, networks, containers and computers. We are on a mission to help developers and 

organizations, such as Cisco, IBM, PayPal, and Tesla, store and analyze real-time data, empowering 

them to build transformative monitoring, analytics, and IoT applications quicker and to scale. InfluxData 

is headquartered in San Francisco with a workforce distributed throughout the U.S. and across Europe.  

 

Learn more. 

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Additional case studies 

Join the InfluxDB community 

  799 Market Street San Francisco, CA 94103 (415) 295-1901 www.InfluxData.com Twitter: @InfluxDB Facebook: @InfluxDB   

 

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