⬜️ Tempo, incubated by Stripe and Paradigm, launched its mainnet — with Mastercard already in the initial partner set.

But the real shift isn’t the launch.

Tempo moves account abstraction, fee sponsorship, and batch execution into the protocol itself — turning what is usually middleware into default behavior for payments.

That changes how stablecoin systems can be built: payroll, cross-border settlement, and high-frequency disbursements don’t rely on external coordination layers.

Mastercard’s involvement fits into that direction — not as a product rollout, but as early positioning around where stablecoin infrastructure is heading.

➡️ Read full article on X

₿itcoin ecosystem overview

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⚡️A Solana transaction can get accepted by RPC and still never land

We wrote up the full flow from wallet tap to confirmation: where transactions drop, what happens between send and confirmation, and why priority fee alone doesn't fix landing.

😋 Read on Telegraph

🖤 Read on htw.tech

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❤️ On Solana, attackers do not always need to touch your program. Sometimes the easier target is the RPC layer around it.

We covered 7 common RPC attack vectors, from leaked endpoints to fragile streams and unsafe transaction submission, and what a hardened Solana RPC path should actually include.

🥳 Read on Medium

🖤 Read on htw.tech

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🟩 We're launching Supanode — HighTower's Solana infrastructure now has its own home.

If you're running a bot, indexer, dApp, alerting system, trading setup, or backend that depends on fast and reliable Solana data, this is for you.

What's inside:
• RPC
• Yellowstone gRPC
• historical data
• indexing support
• transaction landing infra
• dedicated production setups

You don't have to run the full stack yourself just to get stable Solana infrastructure.

➡️ Docs, services, pricing, and setup options:
https://supanode.xyz

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🟩 Free infra for builders on Solana & Hyperliquid

The Supanode Builder Program gives teams 3 full months of free shared endpoints. If your bot, indexer, dApp, trading setup, or backend needs reliable infrastructure on Solana or Hyperliquid, this is for you.

What's included:
• shared RPC and gRPC endpoints
• data access
• direct support from our infra team

No need to stand up your own nodes just to start building on something stable.

👉 Tell us what you're building and what infra you need: Apply here

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🟩 RPC, streaming, indexing, landing, dedicated nodes: Supanode covers Web3 infra across Solana, Hyperliquid, Polymarket-related workflows and EVM chains.

If you're building, testing or scaling, start here:

➡️ Builder Program — 3 months of free shared infra

➡️ 48h trial — for production workloads

➡️ Services, docs & limits

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🟩 Solana API means different things depending on who is debugging it

Frontend usually just needs an endpoint URL.

Infra teams look at the same layer and see limits, retries, WebSocket behavior, and provider choices.

That gap is where production issues start.

➡️ Read the practical guide

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🟩 The frontend bundle is the easiest place to expose a Solana RPC key

Bots reuse the endpoint, quota burns, users hit 429s, and the incident starts looking like provider latency.

Learn what to check before this becomes a production problem: backend proxies, method allowlists, key separation, confirmation tracking, and WebSocket recovery.

➡️ Read the Solana RPC endpoint security guide

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🟩 Solana RPC infrastructure, from endpoint URL to production setup.

A practical map of what sits behind that URL: public access, managed RPC, dedicated nodes, streaming, and production tradeoffs.

👉 Read the Solana RPC infrastructure guide

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🟩 Building trading infra on Solana?

Speed there is a property of the full path, from event detection to confirmed execution.

RPC latency matters, but so do streams, fee logic, submission paths, and confirmation tracking.

➡️ Read our guide to sniper bots and what actually decides execution

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🟩 Planning to run a Solana app on a free RPC endpoint?

Free RPC is a good shortcut while failures are cheap: demos, scripts, devnet work, internal read-only tools.

The risk starts when it becomes part of the product path. Real users notice stale balances, stuck confirmations, dropped WebSocket subscriptions, 429s, exposed browser keys, and heavy methods hitting limits.

Our guide covers what to check before committing to a free endpoint, how public RPC differs from provider free tiers, and when managed or dedicated Solana RPC becomes the safer option.

👉 Read the free Solana RPC guide

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🟩 Does your Solana trading bot use the same RPC path for reads and writes?

It works fine, right up until a trade fails and nobody can tell which layer dropped it.

The read path needs broad visibility: account updates, pool state, quotes, logs, WebSocket or gRPC streams, reconnect recovery, and sometimes historical context.

The write path is a narrower problem. It needs a fresh blockhash, simulation, compute-unit limits, priority fee logic, a controlled sender path, retry rules, and confirmation tracking.

When both paths share the same endpoint and client, very different problems collapse into one vague "RPC issue": stale quote, stream gap, underpriced transaction, expired blockhash, or a sendTransaction response that returned a signature without the trade ever landing.

For a production bot, separating reads from writes is mostly about control. The system needs to know whether to re-quote, retry, fail over, rebuild, or stop.

➡️ Read the full trading bot infrastructure guide

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🟩 Before you raise Solana priority fees again, check what you are actually paying for

A higher CU price is only half of the fee equation. The other half is the compute-unit limit you request.

At the network level:

total network fee = base fee + priority fee
base fee = signatures × 5,000 lamports
priority fee = ceil(CU price × CU limit / 1,000,000)

For a transaction with 1 signature, a CU price of 50,000 micro-lamports, and a requested CU limit of 300,000 CUs, the priority fee is:

ceil(50,000 × 300,000 / 1,000,000) = 15,000 lamports

After adding the 5,000 lamport base fee, the total network fee is 20,000 lamports, or 0.00002 SOL.

The practical detail is that priority fee is calculated from the requested CU limit, not from the compute the transaction actually consumes.

If simulation shows that a transaction usually needs around 180,000 CUs, but the app requests 600,000 by default, the priority fee is still charged on 600,000. Some margin is useful, but an oversized margin becomes repeated overpayment.

For production flows, fee tuning usually means simulating first, setting a realistic CU limit with a controlled buffer, estimating CU price dynamically, and checking whether higher spend actually improves landing.

👉 Read our full guide

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🟩 Choosing a low-latency Solana RPC provider?

Do not start with the homepage number

The better starting point is where your workload runs and what it actually does.

A provider page can show regions, uptime, and latency, but your backend may be in a different cloud region, using heavier RPC methods, sending bursts of requests, tracking confirmations, or relying on fresh streams.

A useful benchmark should come from the same VPS or cloud region as the app, use the methods the app actually calls, and measure p50, p95, and p99 under realistic concurrency.

It should also include burst traffic, because 429s, stream delay, slot freshness, and confirmation tracking issues often stay invisible in clean single-request tests.

➡️ Read the full guide

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