This Is Your SQL Server on Machine Learning

This Is Your SQL Server on Machine Learning

delta bravo, sql server machine learning, database machine learning, ai

Applying Machine Learning models to database management turns the old paradigms upside down. Folks of a certain age remember the old “this is your brain on drugs” commercials from the 80s. For this post, we are going to borrow from this analogy to observe your SQL Server on Machine Learning.

What Is the Benefit of Applying Machine Learning Models to SQL Server?

Machine Learning enables you to:

  • Predict performance trends, capacity and potential security and/or compliance breaches
  • Correlate system spikes and/or anomalous behavior to specific events, actions and code
  • Model all possible fixes and identify the remediation that has the highest likelihood for success

The Power of Influence

It all starts with understanding what factors within the database itself influence each other. This varies with each use case and is influenced by business requirements, maintenance patterns and available system resources. Basically, databases are like people. Would you expect your doctor to prescribe the same medication for three random people just because they share the characteristic of being human?

Delta Bravo’s machine learning algorithms track the relationships between critical performance metrics for each SQL Server database. Here is a heatmap that shows, for this particular database, what metrics influence each other the most. High influence is reflected by a positive number and dark red tones, no influence is zero and gray tones. Negative influence is reflected by negative numbers and black tones.

delta bravo, machine learning, AI for the databaseTranslating Models into Action

For the sake of brevity (further detail is available in our whitepaper), we’re going to focus on the following Use case:

  • Identify a problematic system trend that has NOT reached a threshold*/been alerted on
  • Quantify the trend and verify that trend is going to continue into the future
  • Associate the trend with a specific event, measure impact of event
  • Identify root cause, quantify impact, identify specific action causing impact
  • Provide remediation recommendation

The work you are about to see was performed in 4 clicks (45 seconds) using the Delta Bravo UI. 

Let’s start with a quick view of the Delta Bravo System Health panel for SQL Server Instance DemoSQL-2.

We observe a problematic trend with this SQL Server Instance’s CPU. Is this trend temporary?  Seasonal? Let’s use Predictive Analytics to find out.

We see that the problematic trend is forecasted to continue, growing at a rate of nearly 90% over the next 14 days. However, our system thresholds* have not been hit yet. This means the system is acting in an anomalous fashion. Let’s identify the specific anomalies that are influencing this CPU trend.

delta bravo, predictive analytics for database, SQL Server

In the graphs above, the gray shadow is a machine learning algorithm that represents the “acceptable range” or baseline for system behavior associated with that metric. We see that, while no thresholds have been reached for these metrics, behavior is outside the scope of the baselined “norm.” Why?

By selecting one of the graphs, we’re able to zoom in for more detail. The Blue lines represent specific Events that influenced the rise in that metric.

delta bravo, SQL Server, machine learning

By selecting the line prior to the large red spike, we see that an Object was altered. This procedure impacted Query behavior adversely. We are able to see the code that was used to alter the Object, as well as the quantified impact this change had on Query performance.

delta bravo, machine learning, AI for the database

Using AI to Recommend and Implement a Fix

From here, the AI runs through a series of possible fixes and identifies which ones will have the highest likelihood of success and prioritizes their impact. In this case, the recommended fix is adding a series of Indexes.

delta bravo, database AI, SQL Server machine learning

Similar workflows are applied to Security, Capacity planning and other aspects of database management. We believe the use case is changing; its no longer about monitoring, daily care and feeding. Using Machine Learning and AI to manage large database deployments helps your best people scale where you need them most, and for your systems to run at peak efficiency and performance.

*Delta Bravo has the ability to set thresholds, but we feel this is a dated and reactive way to monitor/manage system behavior.

3 Lessons Learned in Building a Production AI Platform from Delta Bravo

3 Lessons Learned in Building a Production AI Platform from Delta Bravo

Modern Devs Charlotte hosts Delta Bravo team for presentation, live ML coding exercise

Delta Bravo‘s John McAliley and Rick Oppedisano presented to a packed house this week for Modern Devs Charlotte‘s monthly meetup at Wray Ward in uptown Charlotte.

“There’s a ton of interest in AI and Machine Learning,” says Oppedisano, “we want to help people understand where they can start and also learn from our journey. The lessons we’ve learned along the way could save them months of technology evaluation and development time and in some cases, thousands of dollars in system costs.”

Delta Bravo, AI for the Database

Start Small with Familiar Tech

The presentation started with some context of how and why the Delta Bravo AI platform was built. This helped articulate a clear AI use case and also defined the differences between data science, machine learning and artificial intelligence. “Determining if you have an AI use case at all is important,” says Oppedisano. “The ability to clarify that use case and establish the measurables behind it is the first step in the process.”

Once the use case is established, the next step is prototyping. The Delta Bravo team recommends to start small and with a technology you’re already comfortable with. “There are a ton of choices out there and it can be a bit overwhelming,” says McAliley. “There’s likely an option in a tech stack that you’re already working with. Start there to save time and focus on a small, controllable and quickly proven use case.”

Delta Bravo, AI for the Database

Sample Use Case, Live Machine Learning Code Exercise

McAliley followed up with a sample AI use case based on Image Recognition and a live Machine Learning code demo designed to show the differences in accuracy based on data quality and model construction.

A model was established based on metrics that were clearly and visibly defined. “Accuracy is synonymous with credibility,” explained McAliley. “This exercise shows how to get the highest degrees of accuracy, as well as where certain compromises exist and where you begin to get diminishing returns on your model.”

Delta Bravo, AI for the DatabaseThe team also shared Delta Bravo’s functional architecture and provide an example of how AI is used within the platform to recognize, quantify and predict an oncoming database performance problem. This helped the audience visualize the differences in and applications of data science (insight), machine learning (prediction) and artificial intelligence (recommended action).

Lessons Learned

Oppedisano and McAliley shared 3 Lessons Learned from their experience, ranging from technical choices to the importance of data. “The quality of the data you are putting into the model is at the heart of everything,” says Oppedisano. “It’s a classic garbage in, garbage out scenario.” The presentation covered some of the more efficient options available for data cleansing and grouping, as well as the importance of representing the data in a clear, visible manner. “In certain scenarios, the AI process presents the data more efficiently than a human,” says McAliley. “Being able to visualize the data itself, then drill down into insight, correlation and action is important.”

Oppedisano and McAliley shared a fourth “Bonus Lesson” about understanding and managing cost projection. “Machine learning requires a lot of processing,” says Oppedisano. “Its easy for cost to start becoming a factor.”

Delta Bravo, AI for the Database

Feedback and Discussion

“Attendee feedback was very positive,” says Oppedisano, “but the real impression we got was how much opportunity there is in this space.” Several potential use cases and solutions were discussed during and after the presentation, with a lively discussion between the attendees and presenters.

“There’s a lot of passion in the AI community at large,” says Oppedisano. “We want to be a part of bringing that passion and knowledge to the local technology community.”


Interested in topics like this and looking for qualified, professional and fun presenters? We’d be happy to help!  Click below to connect with us.

Delta Bravo Releases AI for Datacenter-wide Predictive Analytics

Delta Bravo Releases AI for Datacenter-wide Predictive Analytics

AI visualizes and projects data growth trends for precise capacity and cost planning in large enterprise and global deployments.

ROCK HILL, SC –(January 3, 2018) – Delta Bravo, the world’s first AI platform for Database Management, released new capabilities to analyze and predict data growth and cost trends at the Datacenter level.

This new feature will be available to all existing Delta Bravo customers on January 3, 2018 and included in all new subscriptions until March 31, 2018. From April 1, 2018 forward, this feature will only be available in Delta Bravo’s Enterprise service tier.

Delta Bravo, AI for the Database

AI Delivers New Precision around Cloud, Cost Planning

“This new capability empowers CIOs and Infrastructure Managers to spot trends in growth and capacity costs from the datacenter to the database,” says Delta Bravo CEO Rick Oppedisano. “At the highest level, they can spot data growth, cost and performance trends for their entire deployment. They can identify what applications and workloads are influencing performance and cost today, then drill into predictive analytics to quantify future costs and growth trends. Our AI identifies specific optimizations that can change these trends, saving money and extending the life of existing infrastructure.”

Companies evaluating cloud deployments on platforms like Microsoft Azure can also benefit. “Most people don’t know what a DTU is or how to quantify it,” says Oppedisano. “New terminology like this can slow cloud adoption down. Delta Bravo identifies trends driving DTU growth and can help predict the impact on cost as data grows. With this information, its easier to project cloud costs and identify which workloads would make the most financial sense to move to the cloud.”

Data Growth, Shortage of Experts Driving AI Use Case

Explosive data growth is driving unprecedented cost and risk in the datacenter, and there simply aren’t enough people to keep up. Oppedisano explains, “Integration of data into cloud applications, warehouses and other analytics platforms has created a huge maintenance need at the database. That’s left enterprise IT Service Operations teams – whose job it is to manage mission critical applications and infrastructure – struggling to catch up and keep their businesses running smoothly. Our vision of using machine learning to automate and scale Data Service Operations matches the needs of our customers, whether they’re startups, enterprises or large Managed Service Providers.”

About Delta Bravo

Delta Bravo is the world’s first Artificial Intelligence platform for Database Management. Delta Bravo handles the time-consuming work of database management, like trend analysis, performance tuning, security and compliance audits. Delta Bravo’s mission is to help technical resources resolve database issues 90% faster than conventional tools and save users hundreds of hours per year in maintenance time.

Delta Bravo uses data science to analyze massive volumes of database activity and turn them into actionable insights. Our AI Platform observes patterns in customer systems that help us understand how data flows, how it’s being maintained and the impact of its growth on surrounding applications and systems. From these observations, we make specific, actionable recommendations tailored to each individual customer.

Founded in 2016, Delta Bravo is backed by PGE Capital and is headquartered in Rock Hill, SC. For more information visit or follow Delta Bravo on Twitter @deltabravoapp.

Delta Bravo Accepted Into Prestigious SC Launch Program

Delta Bravo Accepted Into Prestigious SC Launch Program

Delta Bravo, SCRA

Delta Bravo Among 7 Firms Selected

SUMMERVILLE, S.C.–(BUSINESS WIRE)–SCRA announced the recent acceptance of seven Client Companies into its entrepreneurial program, SC Launch. Client Companies receive mentoring and support services and may also be eligible for grants, matching funds and investments.

Delta Bravo, the Artificial Intelligence Platform that handles database management for you, was selected.

The SC Launch program provides investments, grant opportunities, mentoring and support to early-stage technology companies. Companies in the program are closely aligned with targeted industries like Advanced Materials/Manufacturing, Information Technology and Life Sciences.

“We are honored to have been selected for SC Launch,” says Delta Bravo CEO Rick Oppedisano. “In the last 8 months, we’ve secured a Series A investment, built and launched a compelling, disruptive product. We are looking forward to leveraging our connection with SCRA to drive our growth in 2018.”

Read the full press release here.


Delta Bravo Database Security: How It Works

Delta Bravo Database Security: How It Works

Delta Bravo Database Security features an instant Security Analysis of all databases connected to the system. Within 2 minutes of launching Delta Bravo, users can understand how their current database security levels stack up to standards ranging from PCI and HIPAA all the way up to the US Department of Defense STIG standards.

Delta Bravo instantly provides a breakdown of the security rule, scripts to validate that condition in your environment and scripts to fix it.


Delta Bravo Database Security is not doing a full IT stack compliance check- our scans are specific to the database we are connected to.  We are only indicating topics which MAY be out of compliance specific to SQL, MySQL and PostgreSQL depending on the type of data which is stored in the databases.


The Sarbanes-Oxley (SOX) Act of 2002 is intended to be a revision of federal securities laws which apply to publicly traded companies. Its stated goal is “To protect investors by improving the accuracy and reliability of corporate disclosures made pursuant to the security laws, and for other purposes”. In short, it makes the companies and their leadership responsible for accurate financial reporting, much of which depends on reliable and secure information systems.

Specific to SQL server, Delta Bravo scans and monitor for the following potential SOX compliance issues:

  1. Access and Authentication: Only people who are authorized to use the system can access it.
  2. Monitoring: The capture of events such as authentication attempts, system and account changes, and backup status.
  3. Data Integrity: Being sure that data is not being illegally modified and is being backed up, archived or retained to preserve its integrity.


The Health Insurance Portability and Accountability Act of 1996 establishes a set of national standards for protecting certain individual health information. The primary goal is to ensure that individual’s health information is properly protected while allowing certain information to be securely shared for the promotion of high quality health care and to protect the public’s health and wellbeing. It covers:

  1. Health plans
  2. Health Care Clearinghouses
  3. Healthcare providers who conduct certain financial and administrative transactions electronically.

In order to meet HIPAA standards, the organization must constantly audit and report all access attempts and events related to the databases which contain sensitive Protected Health Information (PHI) records.

Delta Bravo scans and monitor for the following potential HIPAA compliance issues:

  1. Access and Authentication: Only people who are authorized to use the system can access it.
  2. Monitoring: The capture of events such as authentication attempts, system and account changes, and backup status.
  3. Data Integrity: Being sure that data is not being illegally modified at rest or in transit and is being backed up, archived or retained to preserve its integrity.


Originally released in 2004, the Payment Card Industry Data Security Standard (PCI DSS) applies to all entities involved in payment card processing who store, process or transmit cardholder data or sensitive authentication data. It is intended to minimize the risk of storing credit card data and is overseen by the Payment Card Industry Security Standards Council which is made up of representatives from most major credit card providers.

PCI DSS is made up of twelve security requirements which encompass the entire network. Specific to SQL server, Delta Bravo scans and monitor for the following potential PCI compliance issues:

  1. SQL default usernames and passwords
  2. Protection of cardholder data at rest
  3. Encrypted transmission of cardholder data
  4. Overall security of the system
  5. Restriction of access to cardholder data by business need to know
  6. Authentication access to the system
  7. Monitoring and recording of network access to cardholder data

Delta Bravo Database Security Summary

Delta Bravo Database Security features add instant value for administrators, line of business stakeholders and executives. Within hours, companies can significantly strengthen their security posture at the data tier.

While database security is more important than ever, it’s still an overlooked part of day-to-day administration.  Security does not ship in the box and each application is unique in its SQL Server security requirements.  Developers need to understand which combination of features and functionality are most appropriate to counter known threats, and to anticipate threats that may arise in the future.