As a result of the increase in cloud adoption across all industries, understanding practices and tools that help organizations’ software run efficiently is essential to how their cloud environment and organization operate. However, many companies do not have the knowledge or expertise needed for success. In fact, Puppet’s 2021 State of DevOps Report found that while 2 in 3 respondents report using the public cloud, only 1 in 4 use the cloud to its full potential.
Enter the DevOps movement.
The concept of DevOps combines development and operations to encourage collaboration, embrace automation, and speed up the deployment process. Historically, development and operations teams worked independently, leading to inefficiencies and inconsistencies in objectives and department leadership. DevOps is the movement to eliminate these roadblocks and bring the two communities together to transform how their software operates.
According to a 2020 Atlassian survey, 99% of developers & IT decision-makers say DevOps has positively impacted their organization. Benefits include helping advance their career, and better and faster deliverables. Given the favorable outcome for these developers and IT decision-makers, adopting DevOps tools and practices is a no-brainer. But here are three more advantages to embracing the DevOps movement:
Practices like microservices and continuous delivery allow your business operations to move faster, as your operations and development teams can innovate for customers more quickly, adapt to changing markets, and efficiently drive business results. Additionally, continuous integration and continuous delivery (CI/CD) automate the software release process for fast and continuous software delivery. A quick release process will allow you to release new features, fix bugs, respond to your customers’ needs, and ultimately, provide your organization with a competitive advantage.
While DevOps focuses on speed and agile software development, security is still of high priority in a DevOps environment. Tools such as automated compliance policies, fine-grained controls, and configuration management techniques will help you reap the speed and efficiencies provided by DevOps while maintaining control and compliance of your environment.
3. Improved Collaboration
DevOps is more than just technical practices and tools. A complete DevOps transformation involves adopting cultural values and organizational practices that increase collaboration and improve company culture. The DevOps cultural model emphasizes values like ownership and accountability, which work together to improve company culture. As development and operations teams work closely together, their collaboration reduces inefficiencies in their workflows. Additionally, collaboration entails succinctly communicating roles, plans, and goals. The State of DevOps Report also found that clarity of purpose, mission and operating context seem to be strongly associated with highly evolved organizations.
In short, teams who adopt DevOps practices can improve and streamline their deployment pipeline.
What is a DevOps Pipeline?
The term “DevOps Pipeline” is used to describe the set of automated processes and tools that allow developer and operations teams to implement, test, and deploy code to a production environment in a structured and organized manner.
A DevOps pipeline may look different or vary from company to company, but there are typically eight phases: plan, code, build, test, release, deploy, operate, and monitor. When developing a new application, a DevOps pipeline ensures that the code runs smoothly. Once written, various tests are run on the code to flush out potential bugs, mistakes, or any other possible errors. After building the code and running the tests for proper performance, the code is ready for deployment to external users.
A significant characteristic of a DevOps pipeline is it is continuous, meaning each function occurs on an ongoing basis. The most vital one, which was mentioned earlier, is CI/CD. CI, or continuous integration, is the practice of automatically and continuously building and testing any changes submitted to an application. CD, or continuous delivery, extends CI by using automation to release software frequently and predictably with the click of a button. CD allows developers to perform a more comprehensive assessment of updates to confirm there are no issues.
Other “continuous” DevOps practices include:
Continuous deployment: This practice goes beyond continuous delivery (CD). It is an entirely automated process that requires no human intervention, eliminating the need for a “release day.”
Continuous feedback: Applying input from customers and stakeholders, and systematic testing and monitoring code in the pipeline, allows developers to implement changes faster, leading to greater customer satisfaction.
Continuous testing: A fundamental enabler of continuous feedback. Performing automated tests on the code throughout the pipeline leads to faster releases and a higher quality product.
Continuous monitoring: Another component of continuous feedback. Use this practice to continuously assess the health and performance of your applications and identify any issues.
Continuous operations: Use this practice to minimize or eliminate downtime for your end users through efficiently managing hardware and software changes.
From a comprehensive assessment that measures your current software development and operational maturity to developing a strategy for where and how to apply different DevOps approaches to ongoing management and support, we will be with you every step of the way. Following is what a typical DevOps transformation engagement with us looks like:
Phase 0: Basic DevOps Review
DevOps and assessment overview delivered by our Solutions Architects
Phase 1: Assessment & Strategy
Initial 2-4 week engagement to measure your current software development and operational maturity
Develop a strategy for where and how to apply DevOps approaches
1-2 week onboarding to 2nd Watch Managed DevOps service and integration of your operations team and tools with ours
Phase 4: Managed DevOps
Ongoing managed service, including monitoring, security, backups, and patching
Ongoing guidance and coaching to help you continuously improve and increase the use of tooling within your DevOps teams
Getting Started with DevOps
While companies may understand the business benefits derived from DevOps, 2nd Watch has the knowledge and expertise to help accelerate their digital transformation journey. 2nd Watch is a Docker Authorized Consulting Partner and has earned the AWS DevOps Competency for technical proficiency, leadership, and proven success in helping customers adopt the latest DevOps principles and technologies. Contact us today to get started.
Post 2020, how are you approaching the cloud? The rapid and unexpected digital transformation of 2020 forced enterprises worldwide to quickly mobilize workers using cloud resources. Now, as the world returns to an altered normal, it’s time for organizations to revisit their cloud infrastructure components with a fresh perspective. Hybrid work environments, industry transformations, changing consumer behavior, and growing cyber threats have all effected the way we do business. Now it might be time to change your cloud.
Risk mitigation at scale
Avoiding potential missteps in your strategy requires both wide and narrow insights. With the right cloud computing infrastructure, network equipment, and operating systems, organizations can achieve better risk mitigation and management with cloud scalability. As you continue to pursue business outcomes, you have to solve existing problems, as well as plan for the future. Some of these problems include:
Scaling your cloud platform and infrastructure services quickly to keep up with increasing and/or unexpected demand.
Maximizing cloud computing services and computing power to accommodate storage, speed, and resource demands.
Prioritizing new and necessary investments and delivery models within a fixed budget.
Innovating faster to remain, or gain, competitive advantage.
Overall, to avoid risk, you need to gain efficiency, and that’s what the cloud can do. Cloud infrastructure, applications, and Software as a Service (SaaS) solutions are designed to decrease input, and increase output and effectiveness. The scalability of cloud services allows enterprises to continue growing and innovating, without requiring heavy investments. With continuous cloud optimization, you’re positioned to adapt, innovate, and succeed regardless of the unknown future.
Application modernization for data leverage
Much of the digital transformation started with infrastructure modernization and the development of IaaS as a base line. Now, application modernization is accelerating alongside a changing migration pattern. What used to be simply ‘lift and shift’ is now ‘lift and evolve.’ Enterprises want to collaborate with cloud experts to gain a deeper understanding of applications as they become more cloud native. With a constant pipeline of new applications and services, organizations need guidance to avoid cloud cost sprawl and streamline environment integration.
As application modernization continues, organizations are gaining access to massive amounts of data that are enabling brand new opportunities. This requires a new look at database architectures to make sure you’re unlocking value internally and potentially, externally. While application modernization and database architecture are interconnected, they can also transform separately. We’re starting to see people recognize the importance of strategic cloud transformations that include the entire data footprint – whether it’s the underlying architecture, or the top level analytics.
Organizations are getting out of long-term licensing agreements, monetizing their data, gaining flexibility, cutting costs, and driving innovation, customer value, and revenue. Data is pulled from, and fed into, a lot of different applications within constantly changing cloud environments, which brings both challenges and opportunities. Enterprises must transform from this to that, but the end goal is constantly changing as well. Therefore continuous motion is necessary within the digital transformation.
Changing core business strategies
One thing is for sure about the digital transformation – it’s not slowing down. Most experts agree that even after pandemic safety precautions are eliminated, the digital transformation will continue to accelerate. After seeing the speed of adoption and opportunities in the cloud, many enterprises are reevaluating the future with new eyes. Budgets for IT are expanding, but so is the IT skills gap and cybersecurity incidents. These transitions present questions in a new light, and enterprises should revisit their answers.
Why do you still have your own physical data center?
What is the value in outsourcing? And insourcing?
How has your risk profile changed?
How does data allow you to focus on your core business strategy?
Answering these questions has more enterprises looking to partner with, and learn from, cloud experts – as opposed to just receiving services. Organizations want and need to work alongside cloud partners to close the skills gap within their enterprise, gain skills for internal expansion in the future, and better understand how virtualized resources can improve their business. It’s also a way to invest in your employees to reduce turn-over and encourage long-term loyalty.
Security and compliance
At this point with security, compliance, and ensuring business continuity, enterprises must have solutions in place. There is no other way. Ransomware and phishing attacks have been rising in sophistication and frequency year-over-year, with a noticeable spike since remote work became mainstream. Not only does your internal team need constant training and regular enforcement of governance policies, but there’s a larger emphasis on how your network protections are set up.
Regardless of automation and controls, people will make mistakes and there is an inherent risk in any human activity. In fact, human error is the leading cause of data loss with approximately 88% of all data breaches caused by an employee mistake. Unfortunately, the possibility of a breaches is often made possible because of your internal team. Typically, it’s the manner in which the cloud is configured or architected that creates a loophole for bad actors. It’s not that the public cloud isn’t secure or compliant, it’s that it’s not set up properly. This is where many enterprises are outsourcing data protection to avoid damaging compliance penalties, guarantee uninterrupted business continuity, and maintain the security of sensitive data after malicious or accidental deletion, natural disaster, or in the event that a device is lost, stolen or damaged.
Next steps: Think about day two
Enterprises who think of cloud migration as a one-and-done project – we were there, and now we’re here – aren’t ready to make the move. The cloud is not the answer. The cloud is an enabler to help organizations get the answers necessary to move in the direction they desire. There are risks associated with moving to the cloud – tools can distract from goals, system platforms need support, load balancers have to be implemented, and the cloud has to be leveraged and optimized to be beneficial long-term. Without strategizing past the migration, you won’t get the anticipated results.
It can seem overwhelming to take on the constantly changing cloud (and it certainly can be), but you don’t have to do it alone! Keep up with the pace and innovation of the digital transformation, while focusing on what you do best – growing your enterprise – by letting the experts help. 2nd Watch has a team of trusted cloud advisors to help you navigate cloud complexities for successful and ongoing cloud modernization. As an Amazon Web Services (AWS) Premier Partner, a Microsoft Azure Gold Partner, and a Google Cloud Partner with over 10 years’ experience, 2nd Watch provides ongoing advisory services to some of the largest companies in the world. Contact Us to take the next step in your cloud journey!
A lot of enterprises migrate to the public cloud because they see everyone else doing it. And while you should stay up on the latest and greatest innovations – which often happen in the cloud – you need to be aware of the realities of the cloud and understand different cloud migration strategies. You need to know why you’re moving to the cloud. What’s your goal? And what outcomes are you seeking? Make sure you know what you’re getting your enterprise into before moving forward in your cloud journey.
1. Cloud technology is not a project, it’s a constant
Be aware that while there is a starting point to becoming more cloud native – the migration – there is no stopping point. The migration occurs, but the transformation, development, innovation, and optimization is never over.
There are endless applications and tools to consider, your organization will evolve over time, technology changes regularly, and user preferences change even faster. Fueled by your new operating system, cloud computing puts you into continuous motion. While continuous motion is positive for outcomes, you need to be ready to ride the wave regardless of where it goes. Once you get on, success requires that you stay there.
2. Flex-agility is necessary to survival
Flexibility + agility = flex-agility, and you need it in the cloud. Flex-agility enables enterprises to adapt to the risks and unknowns occurring in the world. The pandemic continues to highlight the need for flex-agility in business. Organizations further along in their cloud journeys were able to quickly establish remote workforces, adjust customer interactions, communicate completely and effectively, and ultimately, continue running. While the pandemic was unprecedented, more commonly, flex-agility is necessary in natural disasters like floods, hurricanes, and tornadoes; after a ransomware or phishing attack; or when an employee’s device is lost, stolen, or destroyed.
3. You still have to move faster than the competition
Gaining or maintaining your competitive edge in the cloud has a lot to do with speed. Whether it’s the dog-eat-dog nature of your industry, macroeconomics, or a political environment, these are the things that speed up innovation. You might not have any control over these things, but they’re shaping the way consumers interact with brands. Again, when you think about how the digital transformation evolved during the pandemic, you saw winning business move the fastest. The cloud is an amazing opportunity to meet all the demands of your environment, but if you’re not looking forward, forecasting trends, and moving faster than the competition, you could fall behind.
4. People are riskier than technology
In many ways, the technology is the easiest part of an enterprise cloud strategy. It’s the people where a lot of risk comes into play. You may have a great strategy with clean processes and tactics, but if the execution is poor, the business can’t succeed. A recent survey revealed that 85% of organizations report deficits in cloud expertise, with the top three areas being cloud platforms, cloud native engineering, and security. While business owners acknowledge the importance of these skills, they’re still struggling to attract the caliber of talent necessary.
In addition to partnering with cloud service experts to ensure a capable team, organizations are also reinventing their technical culture to work more like a startup. This can incentivize the cloud-capable with hybrid work environments, an emphasis on collaboration, use of the agile framework, and fostering innovation.
5. Cost-savings is not the best reason to migrate to the cloud
Buy-in from executives is key for any enterprise transitioning to the cloud. Budget and resources are necessary to continue moving forward, but the business value of a cloud transformation isn’t cost savings. Really, it’s about repurposing dollars to achieve other things. At the end of the day, companies are focused on getting customers, keeping customers, and growing customers, and that’s what the cloud helps to support.
By innovating products and services in a cloud environment, an organization is able to give customers new experiences, sell them new things, and delight them with helpful customer service and a solid user experience. The cloud isn’t a cost center, it’s a business enabler, and that’s what leadership needs to hear.
6. Cloud migration isn’t always the right answer
Many enterprises believe that the process of moving to the cloud will solve all of their problems. Unfortunately, the cloud is just the most popular technology operating system platform today. Sure, it can help you reach your goals with easy-to-use functionality, automated tools, and modern business solutions, but it takes effort to utilize and apply those resources for success.
For most organizations, moving to the cloud is the right answer, but it could be the wrong time. The organization might not know how it wants to utilize cloud functionality. Maybe outcomes haven’t been identified yet, the business strategy doesn’t have buy-in from leadership, or technicians aren’t aware of the potential opportunities. Another issue stalling cloud migration is internal cloud-based expertise. If your technicians aren’t cloud savvy enough to handle all the moving parts, bring on a collaborative cloud advisor to ensure success.
Ready for the next step in your cloud journey?
Cloud Advisory Services at 2nd Watch provide you with the cloud solution experts necessary to reduce complexity and provide impartial guidance throughout migration, implementation, and adoption. Whether you’re just curious about the cloud, or you’re already there, our advanced capabilities support everything from platform selection and cost modeling, to app classification, and migrating workloads from your on-premises data center. Contact us to learn more!
If the pandemic and our business applications have one thing in common, it’s the difficulty in preparing for the future. Just as we could not foresee the oncome of the virus, we cannot always precisely determine the capacity required to run our applications effectively, no matter how much we plan.
When demand exceeds your application’s ability and capacity to run efficiently, it’s time to scale.
What is scalability?
Scalability is an application’s ability to increase or decrease overall support and performance in response to the changes in demand. For example, how your company’s website might respond to an increase in visitors is dependent on your application’s scalability. When met with this demand, you want to make sure your application can handle the increase so that it functions properly. Scalability has its limits, and scaling is increasing the capacity of those limits.
The question is: is scaling up or scaling out the right choice for your business?
What is vertical vs. horizontal scaling?
There are two different ways to scale: vertical scaling and horizontal scaling. Vertical scaling, also known as scaling up, is adding more power, or increasing the capacity of a single machine or server for better performance.
For example, you can scale up by adding resources, such as CPU, RAM, or disk capacity to add more processing power to your existing machine. In cloud terms, this translates into increasing the instance type for your application. In the short term, vertical scaling creates a bigger, better machine for an application to run on. Additionally, vertical scaling is data consistent, as your data is stored on a single node / instance. One caveat to scaling up, however, is that it comes with limits to the amount of hardware that can be added to a single machine. Vertical scaling also introduces potential for hardware failures. Vertical scaling is easy in the sense that there is no need for as additions only are made to the machine, but is easier better? Not necessarily.
Horizontal scaling, or scaling out, is when you add more machines or servers to your existing pool of resources. In cloud terms, this is referred to as Auto Scaling where the cloud OS can adjust capacity to demand needs. Rather than adding to a single machine as in scaling up, scaling out is duplicating a current set up and breaking it into separate resources.
Instead of changing the capacity of your existing server you are decreasing the load of the server through additional, duplicate servers. More resources might come appear more complex for your business but scaling out pays off in the long run, especially for larger enterprises. Instead of worrying about upgrading hardware as with vertical scaling, horizontal scaling provides a more continuous and seamless upgrading process.
Which type of scaling is right for your business?
There are pros and cons to both horizontal and vertical scaling, however, horizontal scaling is currently trending due to its reliability and efficiency. Vertical scaling is simpler, while horizontal scaling may prove to optimize your business operations in the long run. Most commonly, business choose to scale out. Regardless of the environment a business operates in, scaling up requires downtime, which can be inefficient for a business’s operations.
There are a several factors to consider when determining the scaling method right for you:
Flexibility: Horizontal scaling allows for flexibility because you can determine the configuration for your setup that optimizes cost and performance for your business needs. Costs are not optimized when scaling up, as you pay for the set price of the hardware.
Upgrades: With vertical scaling, hardware additions can only be upgraded to a limited extent. Horizontal scaling allows for continuous upgrades since you are not dependent on a single piece of equipment.
Redundancy: Another benefit that comes with horizontal scaling is there is no single point of failure distributed with a cloud environment. If your servers fail, the load balancer redirects the request to a different one of your servicers. Vertical scaling, on the other hand, has a single point of failure meaning if the machine goes down, the application goes down with it. Transitioning to the cloud through horizontal scaling eliminates the potential for this problem.
Cost: While vertical scaling may come with a lower upfront cost compared to horizontal scaling, horizontal scaling optimizes cost over time.
Choosing a scaling method that meets your business needs may seem like a complicated choice, but it does not have to be. 2nd Watch is an AWS Premier Partner, a Microsoft Azure Gold Partner, and a Google Cloud Partner providing professional and managed cloud services to enterprises. Contact Us to take the next step in your cloud journey.
As a cloud consulting company, we witness enterprise clients with a lot of data; and typical for most of these clients is that data is siloed with universal access to the information not easily transparent. Client libraries are essentially islands of misfit toys.
During an internal hackathon, Nick Centola and I decided to take up the challenge of creating an enterprise class solution that would extract, transform and load (ETL) data from multiple sources to a data warehouse, with the capability of performing advanced forecasting and in turn be 100% serverless by design that inherently keeps running cost to a minimum.
We decided to keep the scope relatively simple and used the publicly available Citi Bike NYC dataset. The Citi Bike NYC dataset has monthly trip data exported as CSV files and public and a near real-time API, which from our experience is a pattern we often see in enterprises. The diagram below represents what we were trying to achieve.
Extract Transform Load (ETL)
At 2nd Watch, we love Functions-as-a-Service (FaaS) and Cloud Functions as we can create very scalable solutions, have no infrastructure to manage, and in most instances, we will not have to worry about the cost associated with the Cloud Functions.
There were two ETL jobs to write. One was to take the zipped CSV data from the public S3 trip data bucket and land it in our Google Cloud Storage Bucket for an automated daily import into BigQuery. The other function was to grab data from the stations’ near real-time restful API endpoint and insert it into our BigQuery table.
Nick is most efficient with Python; I am most efficient with NodeJS. As both languages are acceptable production code languages for most organizations we work with, we decided to write a function in our respected preferred languages.
The data that we pulled into BigQuery was already clean. We did not need to enrich or transform the data for our purpose – this is not always the case, and cleaning and enriching data are areas where we usually spend most of our time when building similar solutions for our customers.
We wanted to enable a relatively simple forecast on bike demand on individual stations across New York City. BigQuery ML is incredibly powerful and has more than 30 built-in machine learning models. The model of choice for our use case would be the ARIMA model, which takes time series data as an input. I won’t go into too much in detail on why the ARIMA model is a good model for this as compared to the multitude of google cloud functions; the full form of the acronym describes why; Auto Regressive (AR) Integrated (I) Moving Average (MA).
Bringing it all together, we created our LookML models in Looker and interacted with the data exceptionally easily. We made a couple of heat map-based visualizations of New York City to easily visualize the popular routes and stations and a station dashboard to monitor expected supply and demand over the next hour. With the bike stations API data flowing into BQ every 5 seconds, we get a close-to-real-time dashboard that we can use for the basis of alerting staff of an inadequate number of bikes at any station across NYC.
The station forecast shows the upper and the lower bound forecast for each hour over the next month. We use the upper bound forecast for our predicted “amount of bikes in the next hour” and pull in our available bikes from the real-time API. If you use your imagination, you can think of other use cases where a similar prediction could be relevant; franchise restaurant ingredient forecasting or forecasting at retailers for inventory or staffing needs to service customers – the possibilities are endless.
One of the coolest things we did from Nick and my perspective was to drive model training and forecasting straight from Looker and LookML allowing us to essentially kick off our model training every time we receive new data in BigQuery – all from the convenient interface of Looker.
As this was a quick prototyping effort, we took a few shortcuts compared to our delivery standards at 2nd Watch. We did not use infrastructure as code, a best practice we implement for all production-ready customer engagements. Second, we decided not to worry about data quality, which would be something we would clean, enrich, and transform based on your documented business requirements. Third, we did not set up telemetry that would allow us to respond to things like slow queries and broken ETL jobs or visualizations.
Is this hard?
Yes and no. For us it was not – Nick and my combined experience accumulates to thousands of hours building and documenting data pipelines and distributed systems. If you are new to this and your data footprint includes more than a few data sources, we highly recommend that you ask for enterprise expertise in building out your pipeline. You’ll need a team with in-depth experience to help you set up LookML as this will be the foundation for self-service within your organization. Ultimately though, experiments like this can serve to create both business intelligence and allow your organizations to proactively respond to events to meet your corporate and digital transformation initiatives.
Do you want to see a demo of our solution, check out our webinars below:
The COVID-19 pandemic has driven change throughout industry. For healthcare and healthcare professionals in general, attention on digital transformation and use of cloud technology has come to the forefront in a convergence of regulatory requirements, changing modes of care, data security threats, and evolving patient expectations.
Accelerating digitalization and identifying best practices for carrying data through to actionable insight has become a necessity. Many organizations have been forced to adjust their I.T. strategies and priorities. So, what is digital transformation in healthcare and what will it look like? According to a 2021 Stoltenburg/CHIME survey, at the top of the list of rearranged priorities among CIOs focused on digital transformation include:
Using digital health to improve patient engagement
Updating or modernizing EHRs for better data flow
Improving data analytics
Of course, healthcare is inherently data driven. “Data drives nearly every aspect of our healthcare industry. It helps identify longitudinal treatment trends, socioeconomic risks, missed payment opportunities and more. The broad scope of all of these inputs illustrates how mission critical it is to use the right information sources, tools and expertise” says James Bohnsack, Sr. VP and Chief Strategy Office of global information company TransUnion Healthcare.
Hospitals and health systems collect and store volumes of medical records and patient health data estimated to be increasing 48% annually. Data collected across admissions, diagnostics, treatment and discharge as well as patient-provider communications represent a rich resource to those looking to improve care and reduce cost. The opportunities for organizational improvement owing to use of this “big data” have never been better. But how many healthcare organizations have designed future-ready systems to effectively move beyond the collection, storage and simple exchanges of data to leverage all the value of that collective data in the form of actionable insights?
In the past, organizations developed reporting capabilities (operational, regulatory, quality, financial) with disparate paths and processing of data. Although we’ve seen improved data collection, processing and access to data analytics among providers, the pandemic forced healthcare providers to quickly leverage new technologies and see a brighter light. Cloud-enabled supply chain tracking and patient scheduling for vaccines provided a clear example of the value of technology in improving workflow efficiency and management.
Digital Healthcare Systems and Software Development
Moving forward, the good news is that healthcare providers and payers today have access to numerous solutions for efficient and effective data sharing, managing, mining and integrating to guide and improve their operational and clinical decision making. As digital transformation in Healthcare accelerates in 2021, cloud computing and data lakes that enable machine learning and artificial intelligence will enhance the way organizations gain value from their vast amounts of data and health information.
Data standardization through use of HL7 FHIR is helping to build secure interoperability. Transforming from disparate sources and types of data to real-time actionable intelligence and insight has the potential for increased cost efficiency.
Data heavy trends such as telehealth and increased patient interaction through mobile applications are poised to push the need for more efficient technology and data flow further. As healthcare organizations continue to advance along the digitalization journey, we’re seeing a number of consistently mentioned priorities and needs in 2021. These include:
Increased digital transformation initiatives with emphasis on flexibility and future readiness
Greater investment in digital technologies that are transformative
Rising attention to compliance and security
Identification of strategies to best manage multi-cloud environments
Application modernization to improve patient engagement and boost productivity
Post-pandemic revisits of business continuity plans
Continued increases in use of telehealth
Continued interest in leveraging Artificial Intelligence (AI) and Machine Learning (ML)
Increased resource needs for technology initiatives
Desire to work with expert partners, not generic suppliers of services
While “89% of healthcare leaders surveyed are accelerating their digital transformation” (MIT Technology Review Study, 2020), most provider organizations do not have the internal resources and expertise to support their initiatives. It becomes critical to success to find expert partners that can provide a premium level of service and engagement.
2nd Watch is ready for your next step in digital transformation
As a partner for AWS, Google Cloud, and Microsoft Azure, 2nd Watch is a trusted cloud advisor. With digital transformation in healthcare accelerating in 2021, we can enable you to achieve your digital transformation objectives and fuel performance improvement while reducing cloud complexity. Whether you’re embracing cloud data for the first time, strengthening compliance and security, or seeking improvements through advanced analytics, our team of data scientists can help. Contact us to discuss your current priorities and explore our full suite of advanced cloud-native capabilities.